F1000Research F1000Research 2046-1402 F1000 Research Limited London, UK 10.12688/f1000research.132031.1 Review Articles Anticancer activities of tocotrienols: A Systematic Scoping Review

[version 1; peer review: 1 approved, 1 approved with reservations]

 Mohamedahmed Shaza M Data Curation Formal Analysis Investigation Methodology Writing – Original Draft Preparation 1 Kamarudin Muhamad Noor Alfarizal Supervision Writing – Review & Editing 1 Ramdas Premdass Supervision Writing – Review & Editing 2 Khalid Ali Qusay Data Curation Methodology Writing – Review & Editing https://orcid.org/0000-0003-0337-0034 1 Sundralingam Usha Data Curation Supervision Writing – Review & Editing 3 Radhakrishnan Ammu Kutty Conceptualization Formal Analysis Methodology Project Administration Supervision Writing – Review & Editing https://orcid.org/0000-0003-2638-907X a 1 Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Sunway, Selangor, 475000, Malaysia Applied Biomedical Sciences and Biotechnology, International Medical University, Kuala Lumpur, WP Kuala Lumpur, 57000, Malaysia School of Pharmacy, Monash University Malaysia, Sunway, Selangor, 47500, Malaysia ammu.radhakrishnan@monash.edu

No competing interests were disclosed.

 14 4 2023 2023 12 402 31 3 2023 Copyright: © 2023 Mohamedahmed SM et al. 2023 This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: The increasing number of cancer cases requires developing newer approaches to treat this disease. One approach uses natural compounds with known anticancer effects, such as tocotrienols. Many cell-based and animal-model studies found that tocotrienols possess potent anticancer activities. However, the exact molecular regulatory mechanism through which tocotrienols exert anticancer actions remains unclear.

Methods: This scoping review analysed data from original research articles reporting on the anticancer effects of tocotrienols on human cancer cell lines published in the last seven years (January 2015 and September 2021) using a systematic scoping review approach. From the initial 619 research papers [ProQuest (n= 61), PubMed (n= 84), Embase (n = 148), Ovid Medline (n =53), Scopus (n = 137), Web of Science (n =136)] identified using pre-defined keywords, only 37 articles met the inclusion and exclusion criteria for this review. Human cancers commonly studied in the 37 research articles include breast, lung, prostate and colorectal cancer cell lines.

Results: The analysis showed that exposing human cancer cell lines to tocotrienols triggered common anticancer mechanisms such as activation of apoptosis and inhibition of proliferation, angiogenesis and cell migration through regulation of key regulatory genes and proteins involved in these pathways.

Conclusions: The findings show that tocotrienols regulate a number of biomarkers that induce cell death and regulate cell cycle in various types of human cancer cells. Further targeted studies are required to map the definite pathways by which T3 exerts their action and to better understand the cellular actions and the regulatory pathways.

 human cancers vitamin E tocotrienols anticancer mechanisms Vitamin E C D Genomics Biomarkers The author(s) declared that no grants were involved in supporting this work. Introduction

Cancers are the second leading cause of death worldwide before age seventy. 1 Cancers may be formed due to gene mutations or critical dysregulation of different cellular survival and death mechanisms, 2 usually caused by injurious agents that affect cellular homeostasis, structures, and organelles. Some of the more lethal cellular disruptions are associated with an injury to the plasma membrane, the mitochondria, the endoplasmic membrane and the nucleus, 3 which can lead to the development of malignancies. Regardless of the advanced management and treatment available, the number of cancer cases reported is steadily increasing. 1 Treating cancers can be complicated as treatments are generally tailored to each patient's needs and health circumstances, including the cancer origin, position, lymph node involvement and metastasis. Cancer treatments are broadly categorized based on the main method of treatment, such as surgical resection, chemotherapy, radiotherapy and hormonal therapy. 4 Most of the therapeutic approaches currently used have well documented complications. For instance, the surgical approach requires hospitalization and wound healing time, including the possibility of experiencing common post-surgical complications. Chemotherapeutics drugs are cytotoxic to most living cells (normal or malignant), causing side effects such as hair loss, fatigue, nausea, different vital organs toxicity and potentially, the of developing drug resistance. Hormonal therapies, on the other hand, increase susceptibility to other cancers along with other complications such as gynecomastia and hirsutism. Hence, the need for newer ways to treat and/or prevent cancer which do not pose as many side effects as observed with current therapies or have the ability to decrease the severity of these side effects.

The evidence in the literature suggests that several natural compounds such as phytochemicals and vitamins are rapidly emerging as promising anticancer agents, where these compounds can be used as therapeutic or adjuvant agents to treat cancers. 5 Examples of phytochemicals include isoprenoid derivatives, phenol compounds, carbohydrate derivatives, fatty acids, amino acids, and minerals. In addition, several studies have reported that plant phytochemicals promote immunity, protect against DNA damage, and regulate cell cycle and proliferation. 5 Vitamin E (Vit E) is a naturally occurring phytochemical that can exist as two isoprenoid derivatives, tocotrienols (T3) and tocopherols (TP). Tocotrienols and TP have similar chemical structures. However, the side chain on TP is saturated, while the side chain of T3 contains three unsaturated bonds. In addition, both TPs and T3 can be found in four distinctive isoforms known as alpha (α), beta (β), delta (δ) and gamma (γ), which are classified based on the position of methyl groups on the chromanol ring of vitamin E. Natural sources of T3 include palm oil, 6 – 8 annatto seeds 9 and rice bran, 10 , 11 while TP can be found in olive oil, soy oil and corn oil ( Table 1).

Sources of tocotrienols and their major components.
Source of Tocotrienols Tocotrienols Tocopherols Reference
Palm oil tocotrienol rich fraction 70% (all T3 isoforms) 30 % 6
Rice bran TRF 61.7% (all T3 isoforms) 13.1% 7 , 8
Annatto bean oil TRF 90% δT3 10% γT3 - 9
Tocotrienol-rich capsules 78.7% (all T3 isoforms) 21.3% 10
Tocotrienol-rich mixture 25.8 %(all T3 isoforms) 6% 11
TRF: tocotrienol-rich fraction; T3: tocotrienol; δT3: delta-T3; γT3: gamma-T3.

The T3 possess potent antioxidant, cardioprotective, neuroprotective and anticancer activities, reported in many in vitro and in vivo studies. 12 Tocotrienols exert anticancer effects mainly through differentially regulating molecular targets responsible for programmed cell death (PCD) signals, angiogenesis and metastasis. 13 The anticancer activity of T3 have been demonstrated in several types of cancers, including breast cancer (BC), 14 , 15 pancreatic cancer, 16 , 17 hepatic cancer, 18 , 19 haematological cancer 20 , 21 and melanoma. 22 , 23 The cytotoxic effects of T3 against cancer cells are triggered via activation of various intracellular signalling pathways such as activation of apoptosis (programmed cell death type I), autophagy (programmed cell death type II), regulation of cell cycle through inhibiting cell cycle progression through cyclin kinase-dependent (CDK), and cyclin D1, and suppression of angiogenesis. Furthermore, T3, may synergize with chemotherapeutic drugs such as statins, 24 celecoxib 25 and tamoxifen, 26 , 27 to augment their efficacy. Combinations of T3 and natural dietary compounds such as ferulic acid (FA) or jerantinine was reported to induce higher anticancer effects. 28 , 29 The cytotoxic effects of T3 on cancer cells suggest that these molecules can potentially be used as an effective tool in cancer treatment.

The aim of this scoping review is to understand the cellular actions and the regulatory pathways on how tocotrienols induce anticancer effects in human cancer cells through analysing the genes and proteins that are commonly affected in these cancer cells following exposure to tocotrienols in research articles published between January 2015 to September 2021.

 Methods Data source and search strategy

This review was carried out according to the guidelines of the Preferred Reporting Items For Systematic Review And Meta-Analysis (PRISMA). 30 Six databases (PubMed, Pro-Quest, Web of Science, Scopus, Ovid Medline and Embase) were searched using Medical Subject Heading (MeSh) and keywords “tumor*”, “gene*”, “protein*”, “tocotrienol*”, “neoplasm”, “cancer,” and “cell line”. Papers reporting on the effects of T3 on various types of human cancer cell lines, with the primary outcome being gene modulation, regulation or amplification and protein dysregulation, were selected for analysis. In addition, the search was restricted to papers published in English in the last five years (January 2015 to September 2021) to use the latest evidence for this study.

 Eligibility criteria

Eligible studies were selected based on the study’s inclusion and exclusion criteria. The inclusion criteria include that the paper must (i) be an original research article reporting on human cancer cell line exposed to T3 and the findings were compared with untreated cells; (ii) reported on the effects of T3 using differential expression genes or proteins. The exclusion criteria were (i) studies, where cancer cells were not directly exposed to T3; (ii) the effects of T3 on the human cancer cells did not report on gene or protein regulation; (iii) in vivo studies; (iv) in silico studies.

 Data extraction

Two step screening approach was used to identify suitable articles. Original articles published up to 30 Sept 2021 were included in the analysis. The articles identified from the six databases (PubMed, Pro-Quest, Web of Science, Scopus, Ovid Medline & Embase) were imported and compiled in Endnote software 31 initially to eliminate any duplicate articles, and then the articles were uploaded into Covidence software, 32 an online software used to carry out systematic reviews. The steps used to review imported research articles using the Covidence software is similar to what researchers would do if they were screening the identified research articles manually. Briefly, in the first screening, the title and abstract of each research article was screened to identify suitable articles. Following this, a full text review was performed on the short-listed articles to further narrow the search. In each screening step, two researchers independently screening steps, and any arising conflicts were resolved by a third independent researcher. Then, data extraction was performed using an Excel template. The following data were extracted from each article: origin and type of cancer cell line, dose, duration and type of tocotrienol or tocotrienol isomers the cancer cells were exposed to, gene and protein modulation, regulation or expression as the primary outcome and other outcomes such as (apoptosis, cell cycle arrest, IC50), and, the bibliographic details of the article (e.g., authors, year of publication, journal name).

 Results Search results

The search yielded a total of 619 records from six databases [ProQuest (n= 61), PubMed (n= 84), Embase (n = 148), Ovid Medline (n =53), Scopus (n = 137), Web of Science (n =136)]. The articles were imported into Endnote, a referencing software and after removal of duplicate articles (n=145) from the six databases, there were 474 articles left ( Figure 1). These 474 records were uploaded to Covidence, an online software ( www.covidence.com) that enables researchers to independently screen and review articles. In Covidence, another 151 duplicate articles were identified and removed from the pool, which left 323 articles in the pool. From the title and abstract screening, based on the inclusion and exclusion criteria, a total of 252 articles were excluded. The remaining 96 articles were subjected to full text review, where 59 articles were excluded, leaving a total of 37 studies ( Table 2) that were eligible for data extraction ( Figure 1). Data were extracted using a MS-Excel sheet, and information such as origin and type of cancer cell line, dose, duration and type of T3 used and year of publication were collected ( Table 2). More than half of the research papers were published in the years 2015, 2016 and 2017 (53%) ( Figure 2A). Interestingly half of the reported studies were conducted in China and the United States of America ( Figure 2B)

Flowchart of all the stages of the systematic scoping review according to the PRISMA statement. Genes and proteins that were differentiability regulated in human cancer cells treated with tocotrienols based on findings from the systematic scoping review.
Author, Year Human cancer cell line Cancer type T3 Intervention Genes/Proteins modulated Main outcome Other outcomes (e.g., apoptosis, cell cycle, IC50)
Sazli et al., (2015) 47 HepG2 Hepato-cellular carcinoma γT3 70 μM (48 hrs) PRX4 ↓

Anti-proliferative effects due to oxidative distress activation.

Regulated at the protein level

Chen et al., (2015) 50 HL-60 Acute myeloid leukaemia γT3 10, 20 or 30 μM (12 hrs) GLO1, HMGCR, N-RAS, H-RAS, K-RAS, RAF-1, p-AKT, p-ERK ↓

↓ Ras/PI3K/Akt/NF-κB and Ras/Raf/ERK/NF-κB pathways responsible for cholesterol synthesis

Suppression of HMGCR and GLO1 by inactivation of Ras/PI3K/Akt/NF-κB and Ras/Raf/aERK/NF-κB pathways

Gu et al., (2015) 33 CSC from MCF-7 ER + BC γT3 1-5 μg/mL (7-8 days) SHP2, P- SHP2, H-RAS, K-RAS, p-ERK ↓

Dose-dependent inhibition of mammospheres from 1-5 μg/mL

At 5 μg/mL, the growth of the sphere was completely inhibited

Inhibition of SHP2 in a dose-dependent manner and downstream regulation of RAS/ERK pathway

CSC from Hela Cervical adeno-carcinoma
Ryosuke et al., (2015) 9 PC3 Androgen--independent prostate cancer Mixed T3 (90% δT3 and 10% γT3) 10, 20 μg/mL (24 hrs) p-SRC, p-STAT3 ↓

Caused G1 arrest in the cell cycle,

Induced apoptosis

Inhibited phosphorylation/activation of Src and Stat3 in a dose-dependent manner

Parajuli et al., (2015) 34 MCF-7 ER + BC γT3 0-8 mM (96 hrs) P27 (CDKN1B) ↑

Reduced c-Myc.

No change in Myc regulation or cMyc mRNA levels

Inhibition in PI3K/AKT/mTOR and RAS/MEK/ERK signalling pathways.

c-MYC, p-RB, E2F1, CDK4, cyclin D1 (CCND1), FBW7, p-GSK3 α/β, p-AKT, PI3K, p-MTOR, p-ERK 1/2, p-MEK 1/2 ↓
Shibata et al., (2015) 55 DLD-1 CRC δT3 0–20 μM (12, 24 or 48 hrs) under hypoxia/normoxia conditions) P21 (CDKN1A), P27 (CDKN1B), CASP3, CASP9 ↑

δT3 induced dose- and time-dependent apoptotic and anti-proliferative effects on human colorectal cancer cells.
HIF-1α, AKT, CDK4 ↓
Wang et al., (2015) 63 MiaPaCa-2 Pancreatic cancer δT3 50 μM (12 hrs) EGR-1, BAX, SLC20A1, SPRY4, ARRDC3, JUN CFLAR, CAPZA2 ↑

δT3 IC 50: 50 μM for MiaPaCa-2 cells

δT3 regulation of EGR-1 is mediated by JNK-c-Jun signalling pathway.

In the presence of δT3, EGR-1 induces the expression of Bax (a proapoptotic protein), permitting δT3-induced apoptosis

RGS22, SERPINA3, DOCK11, GJA7, GBP2, SLCO2A1, CCL14 ↓
Tiwari et al., (2015) 37 MCF7 ER + BC γT3 40 μmol/L (6,12 & 24 hrs) LC3B-I, LC3B-II, BEC-1, ATG5, ATG12, LAMP-1, Cathepsin-D, BAX, CASP3, PARP, BIP, IRE1, p-ERK, p-elf2α, ATF-4, CHOP, TRB3, P38, p-JNK 1/2 ↑ (both cell lines)

Induced autophagic cell death signals

Endo reticulum triggered apoptosis.

MDA-MB-231 TNBC
BCL2, p-ERK 1/2 ↓ (both cell lines)
Wang et al., (2015) 38 MDA-MB-231 TNBC δT3 0,10, 30, 100 μM (24 hrs) miR-429 ↑

Inhibition of cell proliferation and in- duction of apoptosis in TNBC
MDA-MB-468
Burdeos et al., (2016) 48 HepG2 Hepatocellular Carcinoma γT3, δ T3 5, 10,15, 20 μM (12-24 hrs) GRB2, SOS1, cellular- SRC (c-SRC), SHC2, HRAS, p-SHC ↓

IC50 estimated btw 15-20 μM for γT3 & δT3

Down - regulating upstream signalling genes and proteins of Ras-Raf-MEK-MEK pathway

Comitato et al., (2016) 40 Hela Cervical adenocarcinoma TRF, 10 μg/mL p-IRE-1α ↑ (δ T3) in Hela cells

The number of genes regulated by different T3s isomers are γT3;(177 genes), δ T3;(147 genes) b α T3; (21 genes).

T3 isomers and TRF activated a proapoptotic effect in Hela cells as early as 12 hours (10 μg/ml).

Endo-reticulum mediated apoptosis

MCF7 ER + BC αT3 5 μg/mL CASP12& CASP8 ↑ (δ T3, TRF, γT3) in Hela cells
γT3 5, 10, 20 μg/mL CASP9 ↑ (δ T3) in Hela cells
δT3 5 &10 μg/mL REBF1, SCD & LPIN1 ↓ (α T3, δ T3, γT3)
HSPA5, ASNS, PHLDA1, GDF15& sXBP1 ↑ (δ T3, γT3)
SREBF2, CDKN1A& ID2, ↓ (δ T3, γT3)
CND1, CHAC1, DNAJB9, FAS, GEM, GFPT1& XBP-1 ↑ (γT3)
GSK3B, DNAJC10& c-JUN ↓ (δ T3)
DF2L1, BCR, TRIB3& FAM129A ↑ (δ T3)
Eitsuka et al., (2016) 56 DLD-1 CRC δ T3 10-12.5 μM (72 hrs) Human TERT (hTERT) mRNA ↓

FA alone did not inhibit DLD-1 cells proliferation

Combined FA and δ T3 decreased the expression of hTERT more than δ T3 alone

FA 20 μM (72 hrs) hTERT ↓
Khallouki et al., (2016) 35 MCF-7 ER + BC δ-T3 500 μM (16 hrs) TGFα, PR, Ps2 ↑

δ-T3 activated the transcription of endogenous genes known to be under the control of ERα.

Inhibited the proliferation of both ER + and ER - BC.

HELN cells (HELA cells transfected ERα or Erβ) Cervical cancer
Montagnani et al., (2016) 52 BLM (NRAS mutated) Melanoma δ-T3 20 μg/mL (18 hrs) c- CASP3, IRE1α, ATF4, BIP, p-EIF2α, p-ERK, RE1α, PDI, BAX, BCL2, PARP, CASP4 ↑ (both cell line)

10-20 μg/mL of δ-T3 is cytotoxic to BLM and A375 melanoma cell lines (24hrs-48hrs)

Induction of apoptosis via activation of ER stress in melanoma cells

A375 (V600E BRAF mutated)
ERO1α ↑ A375 cells
Abubakar et al. (2016) 57 U87MG GBM δ-T3 3.12 +/- 1.26 μg/mL (72hrs) CASP3 ↑ (both cell line)

δT3 & jerantinine B induced concurrent synergistic inhibition of cancer cell growth.
HT29 CRC 5.71 +/-1.23 μg/mL (72hrs) CASP8 ↑ (both cell line)
Prasad et al., (2016) 60 HCT 116 (mutated K-ras) CRC γT3 10,25,30 μM (24 hrs) CCND1, MMP9, SURVIVIN, c-IAP-1, c-IAP-2, cellular MYC (cMYC), CXCR4, VEGF, NF-KB ↓

γT3 enhanced capecitabine apoptotic activity.
HT-29
Caco-2 (wild type K-ras)
Huang et al., (2017) 11 VCaP cells Prostate cancer αT3 20 μM (24 hrs) P21 (CDKN1), P27 (CDKN1) ↓

The IC50; ±8 and 49±15μM forα-, δT3 and γT3, respectively, for 24 hrs.

δT3 exhibited more potent cytotoxic effects.

Cell cycle arrest.

γT3 20 μM (24hrs) Cyclin D1 (CCND1), Cyclin A (CCNA) ↑
δ-T3 10 μM (24 hrs)
Lee et al., (2017) 51 K562 Chronic myeloid leukaemia δ-T3 8.04 μg/mL (72 hr) BAD, BCL2L1, BNIP, HRK, MCL1, APAF1, BIRC3, NOD1, NOL3, PYCARD, CASP7, CASP8, CASP9, GADD45A, TP53, TP73, CD40, FAS, TNFERSF10B, TNFERSF1A,TNFERSF9, CD70, FASLG& DAPK1 ↑

IC 50 for δ-T3 was (8.04 μg/mL)

δ-T3 significantly regulated the expression of several genes that promote and regulate apoptosis

Rajasinge et al., (2017) 10 H520 NSCLC squamous cell carcinoma TRF 0.04, 0.08 and 0.12 mg/mL (48 hrs) NOTCH-1, SURVIVIN, PARP, HES-1, BCL-XL ↓ (both cell lines)

A dose-dependent decrease in cell growth, cell migration, tumour invasiveness, induction of apoptosis

inhibition of NF-κB activity, and NF-κB target proteins

A549 NSCLC adenocarcinoma
Xu et al., (2017) 54 HeLa cells Cervical cancer γT3 30,45 & 60 μM (12-24 hrs) BAX, C-PARP, CASP3,C-CASP9, Cytochrome c (mitochondria) ↑

Cell cycle arrest at G0/G1

Induction of apoptosis

BCL2, Ki67, PCNA ↓
Zappe et al., (2018) 58 Caco-2 CRC αToc 20 IU/mL (48 hrs) MLH1, DNMT1 ↑

Reduced H 2O 2-induced lipid peroxidation in a dose-dependent manner.

Increase the expression of the DNA repair gene MLH1.

DNMT1 expression and global methylation were positively affected,

LINE-1 Methylation induction

T3 5 mg/mL (48 hrs)
T3 2 mg/mL (48 hours)
Kaneko et al., (2018) 41 PC3 Prostate cancer δT3 0-40 μM (12 hours under hypoxic conditions) HIF-1α, HIF-2α ↓

Inhibition of hypoxic adaptation of PC3 stem-like cells in vitro
Rajasinghe et al., (2018) 45 A549 Lung cancer δT3 10, 20, 30 μM (72 hours) miR-451 ↑

δT3 suppressed cell migration, invasion, and adhesion in dose dependent manner in both cell lines
H1299 NSCLC MMP9, NOTCH-1, UPA, HES-1 ↓
Zhang et al., (2018) 62 MGC-803 Gastric adenocarcinoma γT3 0, 15, 30, 45 & 60 μmol/L (24,48 & 72 hrs) MMP2, MMP9 ↓

Inhibition of proliferation, migration & invasion in both cell lines
SGC-7901
Palau et al., (2018) 16 MIA PaCa-2 (K-Ras mutated) Pancreatic carcinoma γT3 40 μM (2,4,6 hrs) SPT, DEGS1, CERS6l, ASM, ARV1 ↑ (all cell lines)

upregulation of ceramide

Induction of apoptosis

Panc 1 (wild type) CERT ↓ (all cell lines)
BxPc3 (K-Ras mutated)    
Dronamraju et al., (2019) 36 MCF-7 ER + BC γT3 4-7 μM (4 days) p-AMPKα, p-AMPKß ↑ (both cells)

IC 50 = 5 μM for MD-MB-231, and 4 μM for MCF-7, in dose dependent manner

reduction in the aerobic glycolysis, reduction in glucose metabolism and glycolytic enzymes HKII, PFKP, PK-M2 and LDH.

MDA-MB-231 TNBC HKII, PFKP, PK-M2, LDH, LKB1, p-FOXO3a ↓ both cell)
AKT, FOXO3, MTOR, PFKFB2& PRKAG1 ↓ (MCF7)
AKT2, FOXO3, MTOR, PFKFB2 SLC2A4 & STK11 ↓ (MDA-MB-231)
MLYCD, PRKAG1, PRKAG2 & STRADA ↑ (MDA-MB-231)
Husain et al., (2019) 59 HCT-116 CRC δT3 50 μMol (24 hrs) E-cadherin, C-PARP ↑ (both cells)

Apoptotic cell death in different colon cancer cell lines

Chemopreventive

SW620 β-catenin, Vimentin, NF-kB/P65, MMP9, VEGF ↓ both cell)
Sun et al., (2019) 61 SGC-7901 Gastric cancer γ-T3 15, 30, 45, or 60 μmol/L (/24 hrs) PP2A, p-ATM ↑

Inhibition of NF-κB pathway
NF-kB/p65 ↓
Tang et al., (2019) 43 PC3 cells Prostate cancer (androgen-independent) γT3 10 μg/mL (72 for under serum-free condition) ANG-1/TIE-2 ↓ (combined with Tie-2 inhibitor)

Upregulation of Ang-1

Tie-2 inhibitor increased the cytotoxic effect of γT3

ANG-1 ↓
Ramdas et al. (2019) 39 MDA-MB-231 TNBC γT3 5.8 μg/mL (24hrs) > 30 proteins ↑

γT3 is a proteasome inhibitor
> 30 proteins ↓
Moore et al., (2020) 44 LNCaP Prostate cancer (androgen-sensitive) γT3 10 to 80 μM (6 hrs) ERK, p-c-JUN, Casp3, Casp9 ↑ (both cell lines)

Activation of apoptosis in both cell lines. (RAF/RAS/ERK pathway)
PC-3 Prostate cancer (androgen-independent)
Tupal et al., (2020) 49 HUH-7 Hepatocellular carcinoma αT3 15 ± 0.4 μM (24 hrs) BAX, BID ↑ (αT3 lower than αT3-loaded NLC)

IC 50 αT3: 15 ± 0.4 μM; IC 50 αT3-loaded NLC: 10 ± 0.6 μM

synergistic inhibition of cancer cell growth

αT3-loaded NLC 0.6 μM (24 hrs) mcl-1 mRNA, SURVIVIN, Cyclin-B1 (CCNB1) ↓ (αT3 lower than αT3-loaded NLC)
Fontana, et al., (2020) 42 PC3 Prostate cancer (androgen-dependent) δT3 15 μg/mL (1-24 hrs) c-CASP 3, JNK, P38 ↑ (both cell lines)

mitochondrial activity reduction and O2 consumption

δ-TT-mediated apoptosis, paraptosis and autophagy in PC3 cells

DU145 OXPHOS, c-LOPA1 ↓ (both cell lines)
p-AKT, PINK, PARKIN, P62/SQSTM1 ↑ (PC3 cells)
p-AKT, p-AMPK, MFN2, AKT/MTOR ↓ (PC3 cells)
Idriss et al., (2020) 14 MDA-MB-231 TNBC βT3 10, 20, 30, 40, 50 μM for 24 to 48 hrs Cytochrome c, c-CASP3, c-PARP1 ↑

Activation of apoptosis through a p53-independent apoptotic pathway
BCL2, p-PI3K, p-GSK3 ↓
Ding et al., (2021) 26 MCF-7/Adr (multidrug resistant) ER + BC γT3 25 or 50 μM) for 72 hrs MDR1 ↑

Decrease drug resistance in MCF-7/Adr cells
MDR1/P-GP, P-GP ↓
Shen et al., (2021) 46 CNE1 NPC δT3 10, 20, 40, 80 μM (24 hrs) > 30 genes ↓

Cell cycle arrest in CNE1 cells via the NF- B signalling pathway.

Induction of apoptosis.

> 30 genes ↑
Raimondi et al. (2021) 53 A375 BLM Melanoma δT3 15 μg/mL (6,12 or 24 hrs) AMPK, p-JNK, p-P38, p-ERK1/2 ↑ (both cell lines) Trigger paraptosis in melanoma cells via the Ca 2+/ROS axis

αT3: α-tocotrienol; αToc: d-α-tocopherol; βT3: β-tocotrienol; δT3: δ-tocotrienol; γT3: γ-tocotrienol; TRF: tocotrienol-rich fraction [consist of 78.7% T3 [αT3: 26.7%, βT3: 3.3%, δT3: 10.6%] and 21.3% αToc];

BC: breast cancer; CRC: colorectal carcinoma; CSC: cancer stem cells; ER +: oestrogen-receptor positive; GBM: glioblastoma; NLC: nano-lipid complex; NPC: Nasopharyngeal carcinoma; NSCLC: non-small cell lung cancer; ROS: reactive oxygen species; TNBC: triple negative breast cancer;

↑: upregulation; ↓: down regulation; p: phosphorylated; * Italic font = genes; * regular font= proteins.

 Summary of genes and proteins that were differentially regulated in human cancer cells exposed to tocotrienols and their functions.
Gene/Protein Regulation Description References
AKT ↓ Three closely related serine/threonine- protein kinases (AKT1, AKT2 and AKT3) called the AKT kinase 34 , 36 , 50 , 55
↑ 42
ALDH2 ↑ Aldehyde dehydrogenase, mitochondrial; Aldehyde dehydrogenase 2 family member 39 , 46
AMPK ↑ 5'-AMP-activated protein kinase subunit beta-1; non-catalytic subunit of AMP-activated protein kinase 36 , 42 , 53
ATF4 ↑ Cyclic AMP-dependent transcription factor ATF-4 37 , 52
BAX ↑ BCL2-Associated X Protein 37 , 44 , 46 , 52 , 54 , 63
BCL2 ↓ B-cell lymphoma 2 14 , 37 , 40 , 46 , 51 , 52
BIP ↑ Binding immunoglobulin protein 37 , 52
CASP3 ↑ cysteine-aspartic acid protease (caspase)3 14 , 37 , 44 , 46 , 52 , 54 , 55 , 57
CASP8 ↑ caspase 8 40 , 51 , 57
CASP9 ↑ caspase 9 40 , 44 , 51 , 54 , 55
CCND1 ↓ cyclin D -NK4 cell cycle regulatory module 11 , 34 , 46 , 60
CDKN1B ↑ cyclin dependent kinase inhibitor 1B 34 , 55
CDKN1A ↑ cyclin dependent kinase inhibitor 1A 40 , 46 , 55
CHOP ↑ CCAAT-enhancer-binding protein homologous protein 37 , 52
CDK4 ↓ cyclin-Dependent Kinase 4 37 , 46 , 55
Cytochrome c ↑ cytochrome C 14 , 54
ERK ↓ extracellular-signal-regulated kinase also known as MAPK1 33 , 50 , ↑ 37 , 44 , 52
ERK1 ↓ member of the mitogen, extracellular-signal-regulated kinase also known as MAPK3 34 , 37
↑ 53
FAS ↑ Fas cell surface death receptor 40 , 51
GADD45A ↑ Growth arrest and DNA damage inducible alpha 51
↓ 46
GSK3 β ↓ Glycogen synthase kinase 3beta 34 , 40
GSN ↑ Gelsolin (protein coding gene) 39 , 46
HES1 ↓ hairy and enhancer of split-1 10 , 45
H-RAS ↓ Harvey Rat sarcoma virus 33 , 50
IRE1Α ↑ Inositol-requiring enzyme 1 alpha 37 , 52
JNK ↑ Jun N-terminal kinase, also known as (MAPK8) 37 , 42 , 53
JUN ↑ Jun Proto-Oncogene, AP-1 Transcription Factor Subunit (protein-coding gene) 44 , 63
↓ 40
MMP9 ↓ Matrix Metalloproteinase -9 45 , 59 , 60 , 62
MTOR ↓ mammalian target of rapamycin 34 , 36 , 42
c-MYC ↓ cytoplasmic -myelocytomatosis oncogene product. 34 , 36
NF-κB ↓ Nuclear factor kappa B 59 , 60 , 61
NOTCH1 ↓ Neurogenic locus notch homolog protein 1 10 , 45
P38 ↑ mitogen-activated protein kinases 37 , 42 , 53
P53 ↑ tumour protein P53 or TP53 46 , 51
PARP ↑ poly-ADP ribose polymerase 37 , 52 , 54 , 59
↓ 10
PI3K ↓ Phosphoinositide-3-kinase 14 , 34
RAC1 ↑ Ras-related C3 botulinum toxin substrate 1 39 , 46
SET ↓ SET Nuclear Proto-Oncogene 39 , 46
SURVIVIN ↓ baculoviral inhibitor of apoptosis repeat-containing 5 or BIRC5 10 , 49 , 60
TGFA ↑ Transforming Growth Factor Alpha 35
↑ 46
VEGFR2 ↓ vascular endothelial growth factor receptor-2 59 , 60
HIF1A ↓ Hypoxia-Inducible Factor 1A 41 , 55
SRC ↓ Proto-oncogene tyrosine-protein kinase Src 9 , 48

↓ downregulation; ↑ upregulation.

 Broad analysis of the short-listed records showing the distribution of the publications based on (A) year of publication; (B) country of study; (C) types of human cancer cell lines studied and (D) type of tocotrienol isoform used in the study. Types of human cancer cells lines used

Twelve types of human cancer cell lines were used in the 37 short-listed studies and these include breast cancer, 14 , 26 , 33 – 40 prostate cancer, 9 , 11 , 41 – 44 lung cancer, 10 , 45 nasopharyngeal cancer, 46 hepatocellular carcinoma (liver cancer), 47 – 49 blood cancer, 50 , 51 melanoma], cervical cancer, 33 , 40 , 54 colorectal cancer, 55 – 60 gastric cancer, 61 , 62 brain cancer 57 and pancreatic cancer 63 ( Figure 2C). The top three human cancer cell lines studied appear to be breast, pancreatic cancer, and colorectal cancers ( Figure 2C), while nasopharyngeal and brain cancers were the least studied cancer.

The different isoforms of T3 used in these studies showed prominent anticancer activities ( Figure 2D). While most studies used gamma-T3 (γT3) and/or delta-T3 (δT3) from different sources, only one study investigated the effect of beta-T3 (βT3) ( Figure 2D). That could be due to the relatively stronger anticancer potential of γT3 and δT3 and/or because of the very low concentration of βT3 in nature.

 Mode of action

In general, some of the molecular targets and pathways affected by T3 in humans cancer cell lines appear to be common regardless of the type of the malignancy, such as induction of cell death through apoptosis, 9 , 10 , 26 , 33 , 38 , 40 , 42 , 44 – 46 , 49 – 52 , 54 – 57 , 61 , 63 – 65 followed by inhibiting proliferation through inhibition of cell cycle 9 – 11 , 26 , 34 , 35 , 37 , 40 , 43 , 45 – 49 , 54 – 57 , 60 , 61 , 65 or inhibition of angiogenesis, 43 , 60 cell migration and invasion 10 , 45 , 60 , 62 , 65 ( Figure 3). In a smaller number of studies, the T3 appear to exert the anticancer effects through antiglycolytic effect, 36 suppressing cancer stem cells, 33 antioxidant and synergism with other compounds and antineoplastic therapeutic drugs. 50 A large number of genes and proteins were differentially regulated in the human cancer cells exposed to various forms of T3. We identified 43 biomarkers (genes and proteins) that were reported in two studies or more ( Table 2). Gamma and delta-T3 appear to regulate the expression of most of these genes/proteins ( Figure 4).

Major anticancer mechanisms of tocotrienols identified in this study were inducing cell death via apoptosis (yellow bar); inhibiting proliferation and cell cycle (orange bar); inhibition of angiogenesis, cell migration and invasion (green bar) and other mechanisms, which may include antiglycolytic effect, suppression of cancer stem cells, antioxidant and synergism with other compounds and therapeutic approaches (Blue bar). Venn diagram showing the genes/proteins reported to be regulated by different forms of T3.

(TRF: tocotrienol-rich fraction; αT3: alpha-T3, βT3: beta-T3; δT3: delta-T3, γT3: gamma-T3; T3: tocotrienol)

The pathway enrichment analysis of these 43 biomarkers was carried out using the Metascape bioinformatic tool 66 ( https://metascape.org/gp/index.html) ( Figure 5). According to the software developers, this software can utilize all genes in the genome for the enrichment background. 66 In addition, the software employs several gene ontology sources, including the KEGG pathway, GO Biological Processes, Reactome Gene Sets, PANTHER Pathway CORUM, Wiki Pathways and Canonical Pathways to provide the protein-protein interactions (PPI). To perform the analysis, the 43 biomarkers were uploaded into Metascape. The highest expressed 20 clusters based on enriched terms were used to extract biological information based on their molecular functions and disease bio-pathways curated from KEGG databases, WikiPathways and GO Biological Processes ( Figure 5A). Biomarkers with a p-value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 were collected and congregated into clusters according to their membership similarities ( Figure 5B and 5C). The kappa scores were used to execute hierarchical clustering on the enriched terms and sub-trees (similarity of > 0.3 are considered a cluster). The cluster name represents the most statistically significant term in the cluster ( Figure 5C). The top biological pathways identified in this analysis were cancer pathway followed by apoptosis, gastrin signalling pathway, prostate cancer and VEGFA-VEGFR2 signalling pathway ( Figure 5B). The apoptosis pathway contained 23 of the identified genes ( PARP1, AKT1, XIAP, BIRC5, FAS, ATF4, BAD, BAX, BCL2, CASP3, CASP8, CASP9, GADD45A, DDIT3, ERN1, HRAS, JUN, PIK3CA, MAPK1, MAPK3, MAPK8, TP53, TUBA1C, CDKN1A, MMP9, MYC, RB1, SRC, GSK3B, RAC1, XBP1, CRK, MTOR, HLA-A, RAC2, CCND1, NFKB2, PRKAA1, LONP1, PSEN2, CDK4, CDKN1B, GSN, DYNC1I2, PTPN6, PTPN11, NOTCH1) while the Gastrin signalling pathway contained 20 genes ( AKT1, BIRC5, BAD, CCND1, CASP3, CDKN1A, CDKN1B, CRK, MTOR, GSK3B, HRAS, JUN, MYC, PIK3CA, MAPK1, MAPK3, MAPK8, PTPN11, RAC1, SRC, TP53, BAX, CASP9, ATF4, BCL2, PSEN2, PTPN6, PRKAA1, XIAP, PGR, RB1, RAC2, XBP1, CDK4, GADD45A, DDIT3, HES1, NFKB2, ELF2, PRKAG1, CASP8, MMP9, GSN, ERN1, EPHB2, FAS, PARP1, ATP1A3, TUBA1C, HLA-A, EEF1A1, DYNC1I2, GDF10, NOTCH1) and the VEGFA-VEGFR2 signalling pathway had 24 genes ( AKT1, BIRC5, FAS, ATF4, CCND1, BCL2, CRK, EPHB2, ERN1, MTOR, GSK3B, HRAS, JUN, PIK3CA, PRKAA1, MAPK1, MAPK3, MAPK8, PTPN6, PTPN11, RAC1, SET, SRC, TUBA1C). The genes in the VEGFA-VEGFR2 signalling pathway were essential in the regulation of angiogenesis and proliferation of cells. 67 Some of the molecular targets that reported to be involved in angiogenesis and cell survival such as AKT1, VGF2, CCND1& HRAS were significantly downregulated by T3 in the human cancer cells .

Pathways and process enrichment analysis of the selected genes and proteins.

(A) shows a bar graph of enriched terms across input gene lists, colored by p-values, as shown on the sidebar, while (B) and (C) are protein-protein interaction (PPI) enrichment analysis of the molecular complex detection (MCODE) algorithm has been identified for individual gene lists have been gathered and are shown in (B) the three best-scoring terms by p-value are the functional description of the corresponding components genes are shown in the figure. In (C) MCODE1 represents Chromosomal and microsatellite instability in colorectal cancer and cancer pathways); MCODE2 represents PI3K-AKT-mTOR signaling pathway and therapeutic opportunities and cancer pathways; and MCODE3 represents apoptosis and cancer pathways). The size of the node is related to the protein p-value.

 Protein-protein interaction

Utilizing the highest ten enrichment analysis pathways that were carried out using KEGG (log P is between -42.7857 and -30.1946) 40 common genes i.e. represented in more than two pathways were selected for protein-protein interaction (PPI) analysis. The 40 proteins were uploaded into an online database that can be used for PPI known as the STRING database ( https://string-db.org). Mapping of the 40 genes showed 40 nodes (interactions) along with 225 edges and 63 expected edges with PPI enrichment p-value:< 1.0e-16 analysed at high confidence (0.700) minimum required interaction score. The selected proteins formed three clusters that contained 21,12 and 7 proteins ( Figure 6). The top molecular functional processes with the highest strength were used to determine the functions associated with the annotated proteins. The top functional processes were identified to be histone deacetylase regulator activity (GO:0035033; p= 0.0039, strength: 2.39), cysteine-type endopeptidase activity involved in apoptotic signalling pathway (GO:0097199; p=0.00017; strength: 2.26), BH3 domain binding (GO:0051434; p=0.0064; strength: 2.21), cyclin-dependent protein serine/threonine kinase inhibitor activity (GO:0004861; p=0.00038; strength: 2.09) and MAP kinase activity(GO:0004707; p=0.0011; strength: 1.87). Interestingly, all the molecular functions that regulated initiator cell death were found in one cluster, which includes the mammalian family of mitogen-activated protein kinases (MAPK 1,3 and 8), the caspase family proteins CASP 3,8 and 9, and some cell cycle regulators such as CDK4, CDKN1B and CDKN1A ( Figure 6). Based on the STRING analysis, the mammalian family of MAPK appear to be important targets for T3s to exert their anticancer activity, which is in sync with their pro-apoptotic and cell cycle dysregulation activities. However, MAPKs activity is subjective to the type of the malignancies, and their microenvironment, as these have been found to have dual effects as oncogenes and tumour suppressors in some cancers and related microenvironment. 68 , 69

Protein-protein interactions between the 43 genes/proteins short-listed from the 37 studies analyzed using the STRING database and software.

The dotted line indicates the interactions among the proteins in the three clusters.

 Discussion

The potent cytotoxic effect of T3s is explored and evident in several cancers, yet the exact route through which this action is expressed is still not fully elucidated. In this scoping review, we attempted to understand how T3 exerted their anticancer activity in human cancers and the regulatory mechanisms that govern the anticancer activities. The findings from this study strongly suggest that the most common means by which T3 mediate their effect were through induction of apoptosis and inhibition of proliferation, angiogenesis, and metastasis.

In this review, 25 articles reported that T3 promoted anticancer effects through cell cycle arrest and/or dysregulation of pathways that control cell proliferation and death. One such mechanism was through activation of deoxidation due to overexpression of the PRX4 protein, which causes reduction of hydrogen peroxide and alkyl hyperoxide into water and alcohol and activation of NF-kB. 47 Another mechanism was the ability of T3 to inhibit the expression of the telomerase reverse transcriptase ( TERT) gene in cancer cells. This TERT gene is an essential gene and protein that is involved in cellular proliferation and genetic transcription, which is found in more than 80% of most tumours but not in healthy cells. 70 Delta T3 was reported to suppress the expression of the TERT gene in human colorectal cancer cells. 56 In addition, the cytotoxic effects of T3 can be mediated by decreasing the expression of the hypoxic inducible factor-1α ( HIF-1α) gene in cancer stem cells and in androgen-resistant prostate cancer. 41 It should be noted that HIF-1α is highly expressed in many malignancies and this gene is responsible for various regulatory mechanisms, including hypoxia, angiogenesis and cell proliferation. 41 The antiproliferative effect of T3 on cancer cells is most likely mediated through suppression of proliferative and cell survival pathways such as the VEGFA-VEGFR2 signalling pathway and RAC1/PAK1/p38/MMP2 pathway and activation of apoptosis.

The cell cycle consists of four phases; S phase (DNA synthesis) and M phase (mitotic phase), which are set apart by two gaps (G) phases, G 1 and G 2 ( Figure 7). The cell cycle is regulated by cyclins, which are regulatory blocks of cyclin dependent kinases (CDK) that form heterodimers that promote proliferation and govern the cell cycle checkpoints. The CDK regulate genomic and chromosomal activity in many neoplasms leading to the uncontrolled proliferation and tumorigenesis of cancer cells. The cell cycle has many checkpoints and various types of cyclins are synthesized and dispersed at the cell cycle checkpoints. Checkpoints are regulated by CDK-cyclin complex inhibitors such as p16, p18, p21 and p27, which control downstream activation of the cell cycle pathways, where over-expression can result in cell cycle arrest. 71 The two crucial checkpoints are (i) after DNA replication midway to the end G 1 phase before DNA replication and (ii) at G 2 before chromosomal segregation. The first checkpoint is regulated by CCND1, which is the most common CDK, that phosphorylates the retinoblastoma protein (p RB), allowing the cell cycle to progress while unphosphorylated RB suppresses cell proliferation and keeps the cells at G 0. 72 The CCND1 is overexpressed in several human malignancies such as breast cancer, lung cancer, sarcomas and squamous cells. 73 The p21( CDKN1A) and p27 ( CDKN1B) are key suppressors of CCND1 and crucial to activating cell cycle arrest at G 1. 72 Dysregulation of CDKs is an essential feature of many cancers and provides good targets for drug discovery. Over-expression of CDK in several cancers have become essential targets for drug therapy, such as CDK4/6 inhibitors ribociclib and abemaciclib. 74 , 75

Tocotrienols inhibit the cell cycle at multiple checkpoints causing cell cycle arrest.

T3s regulated the molecular targets demonstrated in this diagram in two or more studies.

In prostate cancer cells, T3 suppressed proliferation and induced apoptosis through dysregulation of several molecular targets such as NF-κB, AKT, STAT3, p53 and p21. 9 , 11 , 72 , 76 The T3 were reported to increase the expression of p21 and p27 and suppress histone deacetylases in human prostate cancer cells. 11 Similarly, the anticancer effect of δT3 on nasopharyngeal cancer (NPC) was mediated through several molecular targets, including downregulation of p21 and upregulation of p16, and downregulation of CCND1, CDK2 and CDK4, which caused cell cycle arrest, possibly due to dysregulation of P16/CDK4/CCND1 signalling pathway. 46 In this review, we found that the members of the cyclin protein family were often downregulated by T3s regardless of the malignancy origin. 11 , 34 , 46 , 49 , 60 In addition, exposure to T3 caused upregulation of p21 and p27 in several human cancer cell lines 11 , 34 , 46 , 55 except in one study, in which γT3 and δT3 suppressed the expression of the p21 gene in cervical cancer cells. 40

The extrinsic pathway of apoptosis is regulated by the death receptors such as the tumour necrosis factor receptors (TNFR), tumour necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) and the TNFR superfamily member-6 (TNFRSF6/FAS). These receptors regulate apoptosis, thus, the fate of the cell. The intrinsic pathway of apoptosis is coordinated by the mitochondria and is set in motion by different proteins that mediate and control cellular homeostasis. One of cancer leading survival mechanisms is decreased expression of pro-apoptotic proteins and increased expression of anti-apoptotic proteins. 77 An example of that critical pro-survival proteins is the BCL2 family, which inhibits several pro-apoptotic proteins that exhibit the homology domain of the BCL2 protein, such as BAX and BAK. Overexpression of BCL2 in cancers is associated with treatment resistance and poor prognosis. 78 Another important protein is the p53 tumour suppressor gene. Lack of p53 allows the progression and proliferation of damaged genetic material. However, activation of p53 upregulates the expression of several genes, such as p21. 79 It can also activate BAX, an essential gene regulator of apoptosis in both intrinsic and extrinsic pathways. 80 , 81 In this review, six research articles reported that exposure to T3 increased the expression of p53 and BAX in human cancer cells ( Figure 8). In addition, the T3 isoforms inhibited the expression of BCL2 in various cancers triggering the expression of several pro-apoptotic proteins and genes causing cell death. 14 , 37 , 40 , 46 , 51 , 52 For example, in cervical cancer cells, T3 reduced the expression of BCL2 and induced apoptosis by upregulating BAX and cytochrome C, a cascade of molecular events expressed during mitochondrial apoptotic pathway activation. 54 In NPC cells, γT3 decreased the expression of the BCL2 gene and BCL2 protein, which in turn activated BAX2 and upregulated CASP proteins 3,8 and 9, causing activation of both apoptotic pathways. 46 FAS, a membrane protein belonging to the death receptors (DR) family, can induce apoptosis by triggering the caspase cascades ( Figure 8). It was reported that exposure to δ-T3 induced cytotoxic cell death in chronic amyloid leukaemia that was mediated by the overexpression of FAS and activation of the extrinsic apoptotic pathway, among other reported genes that are related to the activation of apoptosis. 51 The pro-apoptotic activity of T3 can be mediated through action on different molecular targets that regulate apoptotic cell death ( Figure 8).

Tocotrienols activate apoptosis by targeting several molecules/pathways.

One of the primary mechanisms through which solid tumours survive is their ability to form new vasculature and, thus, gain the ability to proliferate at a higher rate and migrate to a suitable microenvironment. Forming new vessels (angiogenesis) is fundamental for tumour proliferation, sustained nourishment, and oxygen supply. Hypoxia-inducible factor (HIF) is a major factor in the activation of angiogenesis and cancerous cell migration, in search for a better microenvironment. Tumours express abundant amounts of HIF, which in turn regulates the vascular endothelial growth factor (VEGF) and the VEGF receptor transcription responsible for new vasculature. 82 Several anticancer therapies target the molecular signalling pathways responsible of the formation of new vessels to decrease oxygen and nutrition supply to tumours, which will eventually lead to the death signal’s activation and subsequently killing the cancerous cells. Many known treatments exert their cytotoxic action via these processes, such as Sunitinib inhibitor of VEGF receptor tyrosine kinase activity and Bevacizumab, a selective inhibitor of circulating VEGF used in the treatment of refractory ovarian cancer. 83 In this review, the antiangiogenics activity of T3 was among the five most common cellular mechanisms through which T3 exert their actions. Similarly, key molecular targets in tumour angiogenesis, such as HIF1A and VEGFR2, were superseded by T3.

A limitation of this study is that it targeted all types of human cancer cell lines to find common molecular targets and did not target on a single type of human cancer. In addition, the review may have missed papers that did not meet the time scope of this review.

 Conclusions

As reported by the reviewed studies, T3 regulate several underlying cancer cell death mechanisms in different cancer cell lines. Such as a cell cycle regulator and apoptosis inducers. Further targeted studies are required to map the definite pathways by which T3 exerts their action. The reported potent antineoplastic effects in cell culture-based studies and animal studies invite extensive examination of the common mechanism by which T3 exert their action in order for this promising natural compound clinical use.

 Data availability

No data are associated with this article.

 Acknowledgements

The authors would like to thank the Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia for supporting this study.

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Competing interests: No competing interests were disclosed.

 30 8 2023 Copyright: © 2023 López G 2023 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

It is well known that cancer is one of the main causes of death worldwide and it is a challenge to find adequate therapies for its treatment. Several natural compounds such as phytochemicals and vitamins have emerged as promising anticancer agents. The present review article reported by Mohamedahmed et al. focuses on the anticancer properties of tocotrienols, a component of the naturally occurring phytochemical Vitamin E.

The authors performed a systematized analysis of the publications reporting the anticancer activity of tocotrienols in all types of human cancer cell lines, to provide valuable insights into the molecular mechanisms underlying its antiproliferative action. From the analyzed data, the authors highlight that tocotrienols regulate several biomarkers that induce apoptosis and inhibition of proliferation, angiogenesis, and metastasis.

The information gathered here provides a starting point for more specific future studies to fully dissect the pathways by which tocotrienols exert their action. This is a fundamental step in bringing these natural products with promising antitumor activity to the clinic.

Is the review written in accessible language?

Yes

Are all factual statements correct and adequately supported by citations?

Yes

Are the conclusions drawn appropriate in the context of the current research literature?

Yes

Is the topic of the review discussed comprehensively in the context of the current literature?

Yes

Reviewer Expertise:

Drug discovery and development

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

 10.5256/f1000research.144927.r192955 Reviewer response for version 1 Pang Kok Lun 1 Referee https://orcid.org/0000-0003-2219-6297 Newcastle University Medicine Malaysia, Iskandar Puteri, Malaysia

Competing interests: No competing interests were disclosed.

 22 8 2023 Copyright: © 2023 Pang KL 2023 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve-with-reservations

Shaza et al. reviewed the anticancer activities of tocotrienols over several cancerous cells, followed by a bioinformatics analysis of the regulated genes and proteins. Kindly refer to the comments:

Title: Kindly be specific with the "Systematic" and "Scoping review". They are not the same 1 .

Abstract: Please shift the statement "human cancers commonly studied in the 37 research..." to the Results section.

Abbreviations: Please define the abbreviations before using them, and use them consistently throughout the manuscript.

Introduction:

The justification for the use of natural compounds is not concrete. As the authors claimed that chemotherapeutics drugs are cytotoxic to most living cells, causing side effects, etc., then the authors mentioned the natural compounds as promising anticancer agents. Kindly note that plant bioactive compound is the main source for the current mainstream chemotherapeutic agents 2 . So it is kind of contradicting each and other.

Some statements are not supported with citations. 

Table 1: This is confusing as TRF capsules or mixtures in this table are from palm oil. Please include other sources like vegetables, nuts, etc.

Introduction: As the authors mentioned the mechanisms and cellular actions of tocotrienol-mediated anticancer activities, then what is the impact/core value of this review? Justification is weak/not available. What is/are the research gaps? 

 Methods:

The search strategy is not clear. Kindly state the searching string including the Boolean commands. 

The authors stated searching was restricted in the last 5 years but stated 7 years in the abstracts.

Please redo the literature search as the search record was 2 years back. There are several important articles being published ever since 2021.

Confusing exclusion criteria. Exclusion criteria are not simply the opposite of inclusion criteria 3 .

Are the authors considering the studies that employed the combinational treatment of T3 with other chemicals or compounds? 

Data extraction: 

- Who performed the article searching and screening? Who is the 3rd independent researcher?

- Please use "concentration", not "dose"

Fig 1: The number of records is not tally. 323 records screened and 252 records removed, and should leave 71 records, not 96. Besides, 96 records exclude 58 records (2+16+7+1+32) and should be 38 records, not 37. Please check.

 Results:

Table 2: Kindly check the content, please be specific as some (Abubakar et al, 2016) reported the changes of kinetic activities, not protein expression. Please standardise the term writing format as some proteins were written in italicised format (mouse genes?) or full capital letters (human genes?). 

Table 3:

- is there any difference between ERK and ERK1? Or they should be grouped as 1? 

- PARP, caspases are total or cleaved form? How about the phosphorylation status, as proteins like AMPK, AKT, CDK, etc are activated or inhibited upon phosphorylation?

GO and KEGG pathway analysis are not described in Methods

Fig 4, Fig 5 and Fig 6: pathway analysis should be separated for upregulated and downregulated gene or protein set. This is because Metascape and STRING only recognise the gene or protein ID but not their expression or regulation. The authors should run them twice and separate the upregulated and downregulated gene sets and proteins. By performing this, the authors will be able to explain the dual effects of MAPKs, as oncogenes or tumour suppressors.

Results (Protein-protein interaction): How the authors obtained the log P? From the referred studies?

 Discussion:

The authors stated that 25 articles reported the anticancer effects of T3, but the results and Table 1 showed at least 30 articles reporting on the anticancer effects of T3. Kindly correct this. 

Is it making sense by combining and analysing the up- or down-regulated proteins or genes from different cancer cells, tocotrienol types and treatment timeframe? 

What is the contribution or input of GO/KEGG analysis as new knowledge or insights of the anticancer of T3? This will justify whether a GO/KEGG analysis is crucial or beneficial in this review.

Figure 8: Kindly review the content for this figure. For example, T3 overexpressed the FAS, not acting on FAS receptor. Is T3 directly activate the caspases or induce the release of cyt c? 

 Conclusion: Note that the authors only focused on in vitro data. Kindly update the conclusion accordingly.

Is the review written in accessible language?

Yes

Are all factual statements correct and adequately supported by citations?

Partly

Are the conclusions drawn appropriate in the context of the current research literature?

Partly

Is the topic of the review discussed comprehensively in the context of the current literature?

Partly

Reviewer Expertise:

Pharmacology, cancer research, pharmacognosy

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

References : Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol .2018;18(1) : 10.1186/s12874-018-0611-x 143 30453902 10.1186/s12874-018-0611-x : Natural Products as a Vital Source for the Discovery of Cancer Chemotherapeutic and Chemopreventive Agents. Med Princ Pract .2016;25 Suppl 2(Suppl 2) : 10.1159/000443404 41-59 26679767 10.1159/000443404 : Methodology for research I. Indian J Anaesth .2016;60(9) : 10.4103/0019-5049.190619 640-645 27729690 10.4103/0019-5049.190619 Radhakrishnan Ammu Kutty Monash University Malaysia, Malaysia

Competing interests: The authors declare no competing interests.

 31 5 2024

Reviewer comment: Title: Kindly be specific with the "Systematic" and "Scoping review". They are not the same.

Author's response:  Thank you for highlighting this. We know the difference between “Systematic” and “Scoping” reviews. However, the term “systematic scoping” review is an acceptable title for a scoping review, as we have previously published a scoping review with the term "systematic scoping review", which implies a systematic method used to undertake this review.  We would like the title to remain as it is.

Reviewer's comment: Please shift the statement "human cancers commonly studied in the 37 research..." to the Results section

Author's response:  Thank you for highlighting this oversight. We have amended this.

Reviewer's comment: Abbreviations: Please define the abbreviations before using them, and use them consistently throughout the manuscript.

Author's response:  Thank you for highlighting this oversight. We have amended this.

Reviewer's comment: The justification for the use of natural compounds is not concrete. As the authors claimed that chemotherapeutic drugs are cytotoxic to most living cells, causing side effects, etc., then the authors mentioned the natural compounds as promising anticancer agents. Kindly note that plant bioactive compound is the main source for the current mainstream chemotherapeutic agents2. So it is kind of contradicting each and other.

Author's response:  Thank you for highlighting this oversight. We have amended this.

Reviewer's comment: Some statements are not supported with citations

Author's response:  Thank you for highlighting this oversight. We have amended this.

Reviewer's comment: Introduction: As the authors mentioned the mechanisms and cellular actions of tocotrienol-mediated anticancer activities, then what is the impact/core value of this review? Justification is weak/not available. What is/are the research gaps?

Author's response:  Thank you for highlighting this oversight. We have amended this.

Reviewer's comment: The search strategy is not clear. Kindly state the searching string, including the Boolean commands.

Author's response:  Thank you for this comment. We have added the following statement to the paper.

The database was searched using the following terms and Boolean commands such as “tumor* OR neoplasm Or cancer” AND “gene(s)” OR “gene* expression” OR “protein(s)” AND “tocotrienol*’ in all databases.

Reviewer's comment: The authors stated searching was restricted in the last 5 years but stated 7 years in the abstracts.

Author's response:  Thank you for pointing this out. It should have been in the last seven years (not five years). This has been amended.

Reviewer's comment: Table 1: This is confusing as TRF capsules or mixtures in this table are from palm oil. Please include other sources like vegetables, nuts, etc.

Author's response:  Thank you for pointing this out. Table 1 will be moved to the results section as this table highlights the sources of tocotrienols that were mainly used in the papers selected for this scoping review. We will amend the introduction and results sections to reflect these changes.  

Reviewer's comment: Please redo the literature search as the search record was 2 years back. There are several important articles being published ever since 2021.

Author's response:  We cannot do this as this scoping review as we have stated in the methods section that this scoping review will only use papers published in English in the last seven years (January 2015 to September 2021).

Reviewer's comment:  Confusing exclusion criteria. Exclusion criteria are not simply the opposite of inclusion criteria

Author's response:  Thank you for highlighting this. We will include a statement under the “Eligibility criteria” that any papers that did not meet the inclusion criteria will be excluded from this scoping review.

Reviewer's comment: Are the authors considering the studies that employed the combinational treatment of T3 with other chemicals or compounds?

Author's response:  There were a few papers reporting on the combination of T3 and other compounds.  However, we only included the effects reported for T3 (results from combination effects were used) as the focus of this paper is to elucidate the genes and proteins modulated by T3 in human cancer cells.

Reviewer's comment: Who performed the article searching and screening? Who is the 3rd independent researcher?

Author's response:   Dr Shaza and Dr Usha independently performed the article search, screening and data extraction. Prof Ammu was the third independent researcher to resolve any arising conflict. The screening and selection of articles were performed using an online platform (Covidence), which allows independent and unbiased selection of the compiled articles by each reviewer and the conflict resolver.

Reviewer's comment: Please use "concentration", not "dose"

Author's response:  Thank you for the comment. However, we “dose” and “concentration” based on how the authors of the selected papers reported in their paper. 

Reviewer's comment: Fig 1: The number of records is not tally. 323 records screened and 252 records removed, and should leave 71 records, not 96. Besides, 96 records exclude 58 records (2+16+7+1+32) and should be 38 records, not 37. Please check.

Author's response:  Thank you for highlighting the oversight. We have checked our data and found an error and we have rectified this.  We will upload a revised version of Fig 1.

Reviewer's comment: is there any difference between ERK and ERK1? Or should they be grouped as 1?​​​​​​​

Author's response:  We checked the literature and there are at least two forms of extracellular signal-regulated kinase (ERK). In the current manuscript, we reported ERK or ERK1 (Table 3) based on what is reported in each paper.  So, we cannot group all the ERK as one.  We need to follow what was cited in the respective papers

Reviewer's comment: Table 2: Kindly check the content, please be specific as some (Abubakar et al, 2016) reported the changes of kinetic activities, not protein expression. ​​​​​​​

Author's response:  We have re-checked the paper (Abubakar et al., 2016) and confirm that the authors reported fold change in terms of expression (Fig 4 page 114 of this paper). Please see an excerpt from the Figure legend provided.

“Fig. 4. Induction of caspase 8, 9 and 3 enzymatic activities by individual IC50 dose and combined low-dose treatments of δ-tocotrienol with IC20 dose of jerantinine B on (a, b,c) U87MG and (d, e, f) HT-29 cells. Results are presented as percentage fold increase over untreated control cells. Both individual and combined treatments induce caspase 8 and 3 activation on U87MG and HT-29 cells. Whereas, an increased caspase 9 activity is observed in combined treatments (U87MG and HT-29 cells) and U87MG cells treated with IC50 dose of jerantinine B.”

Reviewer's comment: Please standardise the term writing format as some proteins were written in italicised format (mouse genes?) or full capital letters (human genes?).​​​​​​​

Author's response:  Please check the following URL, which states [5]:

“Gene symbol usage

The HGNC endorses the use of italics to denote genes, alleles and RNAs to distinguish them from proteins.”

This paper did not distinguish between human or mouse genes. So, we are not wrong.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494048/#:~:text=Gene%20symbol%20usage,to%20distinguish%20them%20from%20proteins .

Reviewer's comment:  is there any difference between ERK and ERK1? Or they should be grouped as 1?​​​​​​​

Author's response:  We checked the literature and there are at least two forms of extracellular signal-regulated kinase (ERK). In the current manuscript, we reported ERK or ERK1 (Table 3) based on what is reported in each of the papers.  So, we cannot group all the ERK as one.  We need to follow what was cited in the respective papers.

Reviewer's comment: PARP, caspases are total or cleaved form? How about the phosphorylation status, as proteins like AMPK, AKT, CDK, etc are activated or inhibited upon phosphorylation?​​​​​​​

Author's response:  Table 2 actually provided the information requested by the reviewer. Phosphorylation is indicated by “p” next to the affected protein, while cleavage is indicated by “c”. The abbreviation for “p” is shown at the bottom of Table 2. We just realised that the abbreviation for “c” is missing.

Any proteins/genes that were reported to be “upregulated” or “downregulated” are indicated by the ↑ (up) or ↓ (down) symbols.  Again, this is indicated at the bottom of Table 2.

We will add the abbreviation for “c” to the list at the bottom of this table.

Reviewer's comment: GO and KEGG pathway analysis are not described in Methods​​​​​​​

Author's response:  The GO and KEGG pathway analyses are not described in Methods because we did not use these analyses directly. We used another platform known as “Metascape” ( https://metascape.org/gp/index.html#/main/step1 ) , which is described in the Methods.  Metascape has an in-built link to GO and KEGG.

Reviewer's comment: Results (Protein-protein interaction): How the authors obtained the log P? From the referred studies?​​​​​​​

Author's response: We defined the log P based on bioinformatic software (STRING), which has a functional network analysis that provided this information.  Please see a screenshot from the website that provides this information. We hope this clarifies the query.

Reviewer's comment: The authors stated that 25 articles reported the anticancer effects of T3, but the results and Table 1 showed at least 30 articles reporting on the anticancer effects of T3. Kindly correct this.​​​​​​​

Author's response:  We think the reviewer did not understand what is presented in Figure 3.

We were a total of 37 articles that reported on the anticancer effects of T3, that were selected for this scoping review (Table 2 and Figure).

Figure 3 reports on the main mode of action of T3, of which 25 papers reported on apoptosis, 23 on anti-proliferative and cell cycle inhibition, 9 on anti-angiogenesis and 7 on other mechanisms. However, some of these papers reported more than one mode of action of T3 on the cancer cells.  Hence, the total number cannot be 37.

Reviewer's comment: Is it making sense by combining and analysing the up- or down-regulated proteins or genes from different cancer cells, tocotrienol types and treatment timeframe?​​​​​​​

Author's response: This is one way of reporting the data. We are not reporting primary data. We are reporting secondary data i.e. extracting information from published papers, which is what a scoping review is all about.

Reviewer's comment: What is the contribution or input of GO/KEGG analysis as new knowledge or insights of the anticancer of T3? This will justify whether a GO/KEGG analysis is crucial or beneficial in this review.​​​​​​​

Author's response: The author's main goal is to compile and review all The GO and KEGG pathway analyses are not described in Methods because we did not use these analyses directly. We used another platform known as “Metascape” ( https://metascape.org/gp/index.html#/main/step1 ) , which is described in the Methods.  Metascape has an in-built link to GO and KEGG.

Reviewer's comment: Figure 8: Kindly review the content for this figure. For example, T3 overexpressed the FAS, not acting on FAS receptor. Is T3 directly activate the caspases or induce the release of cyt c?​​​​​​​

Author's response:  According to what is reported in (Idriss et al., Table 2), beta T3 can up-regulation of cytochrome c. The same was reported by (Zappe,K et al., Table 2): “γ-tocotrienol specifically promoted cytochrome c release from the mitochondria into the cytosol of HeLa cells”.

Again, we emphasise that this paper is based on secondary data. Furthermore, the exact molecule/receptor that T3 acts via is unclear.

Reviewer's comment: Conclusion: Note that the authors only focused on in vitro data. Kindly update the conclusion accordingly.

Author's response:  Thank you for highlighting this oversight. We have revised this.

Additional references to support the response from authors:

Mazevet M, Moulin M, Llach-Martinez A, Chargari C, Deutsch É, Gomez AM, Morel É. Complications of chemotherapy, a basic science update. La Presse Médicale. 2013 Sep 1;42(9):e352-61.

Sarbaz M, Monazah FM, Eslami S, Kimiafar K, Baigi SF. Effect of mobile health interventions for side effects management in patients undergoing chemotherapy: A systematic review. Health Policy and Technology. 2022 Sep 11:100680.

Marampon F, Ciccarelli C, Zani BM. Biological rationale for targeting MEK/ERK pathways in anti-cancer therapy and to potentiate tumour responses to radiation. International journal of molecular sciences. 2019 May 23;20(10):2530.

Zhou Y, Zhou B, Pache L, et al.: Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 2019; 10(1): 1–10

Bruford, E.A., Braschi, B., Denny, P., Jones, T.E., Seal, R.L. and Tweedie, S., 2020. Guidelines for human gene nomenclature. Nature genetics, 52(8), pp.754-758.