BRAF V600E and SRC mutations as molecular markers for predicting prognosis and conversion surgery in Stage IV colorectal cancer

BRAF mutations and survival with surgery for colorectal liver metastases: A systematic review and meta-analysis

INTRODUCTION

Mutations in the BRAF gene (BRAFmut) are associated with an unfavorable prognosis in patients with metastatic colorectal cancer (CRC). The aim of this meta-analysis was to evaluate the prognosis of colorectal cancer (CRC) patients with liver metastases and the potential benefits of liver resection in patients with BRAFmut CRC.

MATERIAL AND METHODS

A systematic search of PubMed, Cochrane Central Controlled Trials, and Embase databases was conducted on May 31, 2023. The inclusion criteria were as follows:1) reporting of outcomes in patients with BRAFmut CRC who underwent surgery for liver metastases and/or comparison of outcomes between those who underwent and those who did not undergo resection; 2) reporting of survival information as hazard ratios (HR); and 3) publication in English.

RESULTS

34 studies were included. Median follow up was 48 months for prognostic BRAF status meta-analysis. BRAFmut status showed a significantly increased risk of mortality (hazard ratio [HR] = 2.56, 95% confidence interval [CI] 2.04-3.22; P < 0.01) and relapse (HR = 1.97, 95% CI 1.44-2.71; P < 0.01). Resection of liver metastases was associated with a survival benefit (median follow up 46 months). The HR for survival was 0.44 (95% confidence interval [CI] 0.33-0.59; P < 0.01) in favor of surgery.

CONCLUSIONS

and Relevance: Our analysis indeed confirms that BRAF mutation is associated with poor survival outcomes after liver resection of CRC metastases. However, upon quantitatively assessing the survival benefit of surgical intervention in patients with BRAF-mutated CRC liver metastases, we identified a significant 56% reduction in the risk of death.

Mucin phenotype and genetic alterations in non-V600E BRAF-mutated colorectal cancer

Colorectal cancer (CRC) is a heterogeneous disease that develops through stepwise accumulation of genetic alterations and progresses via several distinct pathways. However, the tumorigenesis of CRCs with BRAF non-V600E mutations remains unclear. Here, we aimed to elucidate the tumorigenesis of CRCs with BRAF non-V600E mutations, focusing on differences in mucin phenotype and genetic alterations between CRCs with non-V600E and V600E mutations. We investigated 201 patients with CRC and performed panel testing of 415 genes to identify BRAF mutations. Patients were classified into five mucin phenotypes - large-intestinal, small-intestinal, gastric, mixed, and unclassified - using immunohistochemistry for CD10, MUC2, MUC5AC, and MUC6. BRAF mutations were identified in 24 of 201 patients' samples, of which 13 (6.5%) had a V600E mutation (V600E-mutant) and 11 (5.5%) had non-V600E mutations (non-V600E-mutant). MUC5AC expression was significantly associated with V600E mutations (P = 0.040), while CD10 expression was significantly associated with non-V600E mutations (P = 0.010). The small-intestinal mucin phenotype was significantly associated with non-V600E mutations (P = 0.031), while the mixed mucin phenotype was significantly associated with V600E mutations (P = 0.027). Regarding genetic alterations, focusing on the WNT signaling pathway, APC mutation was significantly associated with non-V600E mutations (P < 0.001), while RNF43 mutation was significantly associated with V600E mutations (P = 0.020). Considering the differences in mucin phenotype and genetic alterations, different modes of tumorigenesis are assumed for CRC with BRAF V600E mutation and non-V600E mutations. These findings are important in understanding the biology and treatment strategies for BRAF-mutant CRC.

SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures

Background

One of the major challenges in precision medicine is accurate prediction of individual patient’s response to drugs. A great number of computational methods have been developed to predict compounds activity using genomic profiles or chemical structures, but more exploration is yet to be done to combine genetic mutation, gene expression, and cheminformatics in one machine learning model.

Results

We presented here a novel deep-learning model that integrates gene expression, genetic mutation, and chemical structure of compounds in a multi-task convolutional architecture. We applied our model to the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE) datasets. We selected relevant cancer-related genes based on oncology genetics database and L1000 landmark genes, and used their expression and mutations as genomic features in model training. We obtain the cheminformatics features for compounds from PubChem or ChEMBL. Our finding is that combining gene expression, genetic mutation, and cheminformatics features greatly enhances the predictive performance.

Conclusion

We implemented an extended Graph Neural Network for molecular graphs and Convolutional Neural Network for gene features. With the employment of multi-tasking and self-attention functions to monitor the similarity between compounds, our model outperforms recently published methods using the same training and testing datasets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04352-9.

Oncological evaluation in the perioperative period using cfDNA with BRAF V600E mutation in patients with colorectal cancer

The detection of circulating cell-free DNA (cfDNA) by liquid biopsy is reported to provide prognostic information in colorectal cancer (CRC). Although the frequency of BRAF V600E mutation in CRC is less than 10%, it is associated with poor responses to conventional chemotherapy. We conducted a prospective study to investigate the relationship between the perioperative mutant allele frequency (MAF) of BRAF V600E and tumor recurrence, and to evaluate the possibility of early detection of recurrence. Among 362 patients who underwent radical resection, cfDNA was extracted from the perioperative blood of 11 CRC patients with BRAF V600E mutation and analyzed using the digital polymerase chain reaction (dPCR) system. The median follow-up time was 22 months, and there were four cases of recurrence. Although there was no correlation between recurrence and the perioperative MAF of BRAF V600E, tumor diameter was correlated with the MAF (p = 0.024), and the MAF increased with time in two patients from whom additional samples were obtained prior to recurrence. In this study, we identified a correlation between the pathological tumor diameter and the MAF, but it was difficult to predict recurrence by measuring cfDNA with BRAF V600E mutation in the perioperative period of radical resection of CRC.

Profiling of host genetic alterations and intra-tumor microbiomes in colorectal cancer

Some bacteria are symbiotic in tumor tissues, and metabolites of several bacterial species have been found to cause DNA damage. However, to date, the association between bacteria and host genetic alterations in colorectal cancer (CRC) has not been fully investigated. We evaluated the association between the intra-tumor microbiome and host genetic alterations in 29 Japanese CRC patients. The tumor and non-tumor tissues were extracted from the patients, and 16S rRNA genes were sequenced for each sample. We identified enriched bacteria in tumor and non-tumor tissues. Some bacteria, such as Fusobacterium, which is already known to be enriched in CRC, were found to be enriched in tumor tissues. Interestingly, Bacteroides, which is also known to be enriched in CRC, was enriched in non-tumor tissues. Furthermore, it was shown that certain bacteria that often coexist within tumor tissue were enriched in the presence of a mutated gene or signal pathway with mutated genes in the host cells. Fusobacterium was associated with many mutated genes, as well as cell cycle-related pathways including mutated genes. In addition, the patients with a high abundance of Campylobacter were suggested to be associated with mutational signature 3 indicating failure of double-strand DNA break repairs. These results suggest that CRC development may be partly caused by DNA damage caused by substances released by bacterial infection. Taken together, the identification of distinct gut microbiome patterns and their host specific genetic alterations might facilitate targeted interventions, such as modulation of the microbiome in addition to anticancer agents or immunotherapy.

Histopathological characteristics and artificial intelligence for predicting tumor mutational burden-high colorectal cancer

BACKGROUND

Tumor mutational burden-high (TMB-H), which is detected with gene panel testing, is a promising biomarker for immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC). However, in clinical practice, not every patient is tested for TMB-H using gene panel testing. We aimed to identify the histopathological characteristics of TMB-H CRC for efficient selection of patients who should undergo gene panel testing. Moreover, we attempted to develop a convolutional neural network (CNN)-based algorithm to predict TMB-H CRC directly from hematoxylin and eosin (H&E) slides.

METHODS

We used two CRC cohorts tested for TMB-H, and whole-slide H&E digital images were obtained from the cohorts. The Japanese CRC (JP-CRC) cohort (N = 201) was evaluated to detect the histopathological characteristics of TMB-H using H&E slides. The JP-CRC cohort and The Cancer Genome Atlas (TCGA) CRC cohort (N = 77) were used to develop a CNN-based TMB-H prediction model from the H&E digital images.

RESULTS

Tumor-infiltrating lymphocytes (TILs) were significantly associated with TMB-H CRC (P < 0.001). The area under the curve (AUC) for predicting TMB-H CRC was 0.910. We developed a CNN-based TMB-H prediction model. Validation tests were conducted 10 times using randomly selected slides, and the average AUC for predicting TMB-H slides was 0.934.

CONCLUSIONS

TILs, a histopathological characteristic detected with H&E slides, are associated with TMB-H CRC. Our CNN-based model has the potential to predict TMB-H CRC directly from H&E slides, thereby reducing the burden on pathologists. These approaches will provide clinicians with important information about the applications of ICIs at low cost.

Therapeutic implications of B-RAF mutations in colorectal cancer

Colorectal cancers (CRC) with B-RAF mutation carry a particularly poor prognosis. In this context, the value of first-line intensified chemotherapy associated with an anti-VEGF (Vascular endothelial growth factor) to treat metastatic CRC has recently been called into question. In patients with mutated B-RAF, the efficacy of first-line anti-EGFR (Epidermal Growth Factor Receptor) associated with chemotherapy for treatment of metastatic CRC is uncertain while that of anti-VEGF has been shown to be effective. The therapeutic pathways involving inhibition of B-RAF activity, although ineffective as monotherapy, have received marketing authorization when used in association with anti-EGFR for second-line treatment of metastatic CRC. Immunotherapy has provided very encouraging results in a recent phase III study in patients with microsatellite instability, irrespective of their B-RAF status. Finally, new therapies, targeting other RAF proteins and other specific receptors are currently under development. Surgery for liver metastases in patients with the B-RAF mutation should be considered whenever possible, after a complete search for peritoneal carcinomatosis and distant metastases, similarly to workup for patients without the B-RAF mutation.

Clinical, Pathological and Prognostic Features of Rare BRAF Mutations in Metastatic Colorectal Cancer (mCRC): A Bi-Institutional Retrospective Analysis (REBUS Study)

Recently, retrospective analysis began to shed light on metastatic colorectal cancers (mCRCs) harboring rare BRAF non-V600 mutations, documenting a distinct phenotype and a favorable prognosis. This study aimed to confirm features and prognosis of rare BRAF non-V600 mCRCs compared to BRAF V600E and BRAF wild-type mCRCs treated at two Italian Institutions. Overall, 537 cases were retrospectively evaluated: 221 RAS/BRAF wild-type, 261 RAS mutated, 46 BRAF V600E and 9 BRAF non-V600. Compared to BRAF V600E mCRC, BRAF non-V600 mCRC were more frequently left-sided, had a lower tumor burden and displayed a lower grade and an MMR proficient/MSS status. In addition, non-V600 mCRC patients underwent more frequently to resection of metastases with radical intent. Median overall survival (mOS) was significantly longer in the non-V600 compared to the V600E group. At multivariate analysis, only age < 65 years and ECOG PS 0 were identified as independent predictors of better OS. BRAF V600E mCRCs showed a statistically significant worse mOS when compared to BRAF wild-type mCRCs, whereas no significant difference was observed between BRAF non-V600 and BRAF wild-type mCRCs. Our study corroborates available evidence concerning incidence, clinicopathologic characteristics and prognosis of BRAF-mutated mCRCs.

ETumorMetastasis: A Network-based Algorithm Predicts Clinical Outcomes Using Whole-exome Sequencing Data of Cancer Patients

Continual reduction in sequencing cost is expanding the accessibility of genome sequencing data for routine clinical applications. However, the lack of methods to construct machine learning-based predictive models using these datasets has become a crucial bottleneck for the application of sequencing technology in clinics. Here, we develop a new algorithm, eTumorMetastasis, which transforms tumor functional mutations into network-based profiles and identifies network operational gene (NOG) signatures. NOG signatures model the tipping point at which a tumor cell shifts from a state that doesn’t favor recurrence to one that does. We show that NOG signatures derived from genomic mutations of tumor founding clones (i.e., the ‘most recent common ancestor’ of the cells within a tumor) significantly distinguish the recurred and non-recurred breast tumors as well as outperform the most popular genomic test (i.e., Oncotype DX). These results imply that mutations of the tumor founding clones are associated with tumor recurrence and can be used to predict clinical outcomes. As such, predictive tools could be used in clinics to guide treatment routes. Finally, the concepts underlying the eTumorMetastasis pave the way for the application of genome sequencing in predictions for other complex genetic diseases. eTumorMetastasis pseudocode and related data used in this study are available at https://github.com/WangEdwinLab/eTumorMetastasis.

Identification of 6 Hub Proteins and Protein Risk Signature of Colorectal Cancer

Background

Colorectal cancer (CRC) is the second most common cause of cancer death in the United States and the third most common cancer globally. The incidence of CRC tends to be younger, and we urgently need a reliable prognostic assessment strategy.

Methods

Protein expression profile and clinical information of 390 CRC patients/samples were downloaded from the TCPA and TCGA database, respectively. The Kaplan-Meier, Cox regression, and Pearson correlation analysis were applied in this study.

Results

Based on the TCPA and TCGA database, we screened 6 hub proteins and first constructed protein risk signature, all of which were significantly associated with CRC patients' overall survival (OS). The risk score was an independent prognostic factor and significantly related with the size of the tumor in situ (T). 6 hub proteins were differentially expressed in cancer and normal tissues and in different CRC stages, which were validated at the ONCOMINE database. Next, 40 coexpressed proteins of 6 hub proteins were extracted from the TCPA database. In the protein-protein interaction (PPI) network, HER1, HER2, and CTNNB1 were at the center. Function enrichment analysis illustrated that 46 proteins were mainly involved in the EGFR (HER1) tyrosine kinase inhibitor resistance pathway.

Conclusion

Studies indicated that 6 hub proteins might be considered as new targets for CRC therapies, and the protein risk signature can be used to predict the OS of CRC patients.

Effectiveness of Scutellaria barbata water extract on inhibiting colon tumor growth and metastasis in tumor-bearing mice

The plant Scutellaria barbata (SB) is commonly used as herbal medicines for treating cancer. The present pre-clinical study aimed to validate the Chinese Pharmacopoeia (CP) recommended dosages of SB water extract (SBW) in treating colon tumors. The content of chemical marker scutellarin in SBW was quantified using UPLC. Mice bearing human HCT116 xenografts or murine colon26 tumors received oral administration of SBW or scutellarin for 4 weeks. Results showed that SBW (615 and 1,230 mg/kg) and scutellarin (7 mg/kg) treatments significantly reduced human xenograft weights by 28.7, 36.9 and 28.8%, respectively. Lung metastasis area could be ameliorated after SBW (615 mg/kg) and scutellarin (7 mg/kg) treatments by 23.4 and 29.5%, respectively. Expressions of colon cancer metastasis-related proteins E-cadherin, Tspan 8 and CXCR4, as well as Src kinase in tumors were first shown to be regulated by SBW. Furthermore, in murine colon26 tumor-bearing mice, SBW (615 mg/kg) and scutellarin (7 mg/kg) treatments reduced the orthotopic tumor burden by 94.7% and lung metastatic tumor burden by 94.1%, respectively. Our findings provided evidences that SBW (at the mouse equivalent dosages to clinical dosages recommended by CP) could exert anti-tumor and anti-metastatic effects in colon cancer animal models.

Src Family Tyrosine Kinases in Intestinal Homeostasis, Regeneration and Tumorigenesis

Src, originally identified as an oncogene, is a membrane-anchored tyrosine kinase and the Src family kinase (SFK) prototype. SFKs regulate the signalling induced by a wide range of cell surface receptors leading to epithelial cell growth and adhesion. In the intestine, the SFK members Src, Fyn and Yes regulate epithelial cell proliferation and migration during tissue regeneration and transformation, thus implicating conserved and specific functions. In patients with colon cancer, SFK activity is a marker of poor clinical prognosis and a potent driver of metastasis formation. These tumorigenic activities are linked to SFK capacity to promote the dissemination and tumour-initiating capacities of epithelial tumour cells. However, it is unclear how SFKs promote colon tumour formation and metastatic progression because SFK-encoding genes are unfrequently mutated in human cancer. Here, we review recent findings on SFK signalling during intestinal homeostasis, regeneration and tumorigenesis. We also describe the key nongenetic mechanisms underlying SFK tumour activities in colorectal cancer, and discuss how these mechanisms could be exploited in therapeutic strategies to target SFK signalling in metastatic colon cancer.

Overcoming Resistance to Therapies Targeting the MAPK Pathway in BRAF-Mutated Tumours

Overactivation of the mitogen-activated protein kinase (MAPK) pathway is an important driver of many human cancers. First line, FDA-approved therapies targeting MAPK signalling, which include BRAF and MEK inhibitors, have variable success across cancers, and a significant number of patients quickly develop resistance. In recent years, a number of preclinical studies have reported alternative methods of overcoming resistance, which include promoting apoptosis, modulating autophagy, and targeting mitochondrial metabolism. This review summarizes mechanisms of resistance to approved MAPK-targeted therapies in BRAF-mutated cancers and discusses novel preclinical approaches to overcoming resistance.