Clinical Implication of Concordant or Discordant Genomic Profiling between Primary and Matched Metastatic Tissues in Patients with Colorectal Cancer

Putative anoikis resistant subpopulations are enriched in lymph node metastases and indicate adverse prognosis in colorectal carcinoma

Anoikis refers to apoptosis induced by the loss of contact with the extracellular matrix. Anoikis resistance is essential for metastasis. We have recently shown that it is possible to quantitatively evaluate putative anoikis resistant (AR) subpopulations in colorectal carcinoma (CRC). Abundance of these multi-cell structures is an independent marker of adverse prognosis. Here, we have quantified putative AR subpopulations in lymph node (LN) metastases of CRC and evaluated their prognostic value and relationship with the characteristics of primary tumors. A case series included 137 unselected CRC patients, 54 with LN metastases. Areal densities (structures/mm²) of putative AR structures in primary tumors had been analyzed previously and now were determined from all nodal metastases (n = 183). Areal density of putative AR structures was higher in LN metastases than in primary tumors. Variation of the areal density within different LN metastases of a single patient was lower than between metastases of different patients. Abundance of putative AR structures in LN metastases was associated with shorter cancer specific survival (p = 0.013), and this association was independent of T and N stages. Abundance of putative AR structures in primary tumors and LN metastases had a cumulative adverse effect on prognosis. Enrichment of putative AR subpopulations in LN metastases suggest that in metastasis formation, there is a selection favoring cells capable of forming these structures. Higher intra-case constancy relative to inter-case variation suggests that such selection is stable in metastasis development. Our findings indirectly support the biological validity of our concept of putative AR structures.

Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients

Purpose: Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors. Methods: Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters. Results: A novel 7-Gene Algorithm based on mutation profiles of seven KRAS-associated genes was identified. The algorithm was able to distinguish non-progressed (responder) vs. progressed (non-responder) patients with AUC of 0.97 and had predictive power for PFS with a hazard ratio (HR) of 16.9 (p < 0.001) in the MSK cohort. The predictive power of this algorithm for PFS was more pronounced in mCRC (HR = 16.9, p < 0.001, n = 388). Similarly, in the TCGA validation cohort, the algorithm had AUC of 0.98 and a significant predictive power for PFS (p < 0.001). Conclusion: The novel 7-Gene Algorithm can be further developed as a biomarker model for prediction of treatment response in mCRC patients to improve personalized therapies.

Comprehensive Imaging Characterization of Colorectal Liver Metastases

Colorectal liver metastases (CRLM) have heterogenous histopathological and immunohistochemical phenotypes, which are associated with variable responses to treatment and outcomes. However, this information is usually only available after resection, and therefore of limited value in treatment planning. Improved techniques for in vivo disease assessment, which can characterise the variable tumour biology, would support further personalization of management strategies. Advanced imaging of CRLM including multiparametric MRI and functional imaging techniques have the potential to provide clinically-actionable phenotypic characterisation. This includes assessment of the tumour-liver interface, internal tumour components and treatment response. Advanced analysis techniques, including radiomics and machine learning now have a growing role in assessment of imaging, providing high-dimensional imaging feature extraction which can be linked to clinical relevant tumour phenotypes, such as a the Consensus Molecular Subtypes (CMS). In this review, we outline how imaging techniques could reproducibly characterize the histopathological features of CRLM, with several matched imaging and histology examples to illustrate these features, and discuss the oncological relevance of these features. Finally, we discuss the future challenges and opportunities of CRLM imaging, with a focus on the potential value of advanced analytics including radiomics and artificial intelligence, to help inform future research in this rapidly moving field.

High Concordance of Genomic Profiles between Primary and Metastatic Colorectal Cancer

The comparison of the genetic profiles between primary and metastatic colorectal cancer (CRC) is needed to enable the discovery of useful therapeutic targets against metastatic CRCs. We performed the targeted next generation sequencing assay of 170 cancer-associated genes for 142 metastatic CRCs, including 95 pairs of primary and metastatic CRCs, to reveal their genomic characteristics and to assess the genetic heterogeneity. The most frequently mutated gene in primary and metastatic CRCs was APC (71% vs. 65%), TP53 (54% vs. 57%), KRAS (45% vs. 44%), PIK3CA (16% vs. 19%), SMAD4 (15% vs. 14%) and FBXW7 (11% vs. 11%). The concordance in the top six frequently mutated genes was 85%, on average. The overall mutation frequencies were consistent with two sets of public data (TCGA and MSKCC). To the author’s knowledge, this is the first study to compare the genetic profiles of our cohort with that of the metastatic CRCs from MSKCC. Comparative sequencing analysis between primary and metastatic CRCs revealed a high degree of genetic concordance in the current clinically actionable genes. Therefore, the genetic investigation of archived primary tumor samples with the challenges of obtaining an adequate sample from metastatic sites appears to be sufficient for the application of cancer precision medicine in the metastatic setting.

Comparison of metastatic castration-resistant prostate cancer in bone with other sites: clinical characteristics, molecular features and immune status

Metastatic castration-resistant prostate cancer (mCRPC) is the lethal stage and the leading cause of death in prostate cancer patients, among which bone metastasis is the most common site. Here in this article, we downloaded the gene expression data and clinical information from online dataset. We found that prostate cancer metastasis in bone is prone to have higher prostate-specific antigen (PSA) and longer time on first-line androgen receptor signaling inhibitors (ARSI). A total of 1,263 differentially expressed genes (DEGs) were identified and results of functional enrichment analysis indicated the enrichment in categories related to cell migration, cancer related pathways and metabolism. We identified the top 20 hub genes from the PPI network and analyzed the clinical characteristics correlated with these hub genes. Finally, we analyzed the immune cell abundance ratio of each sample in different groups. Our results reveal the different clinical characteristics, the immune cell infiltration pattern in different sites of mCRPC, and identify multiple critical related genes and pathways, which provides basis for individualized treatment.

Clinical Application of Targeted Deep Sequencing in Metastatic Colorectal Cancer Patients: Actionable Genomic Alteration in K-MASTER Project

Purpose

Next-generation sequencing (NGS) can facilitate precision medicine approaches in metastatic colorectal cancer (mCRC) patients. We investigated the molecular profiling of Korean mCRC patients under the K-MASTER project which was initiated in June 2017 as a nationwide precision medicine oncology clinical trial platform which used NGS assay to screen actionable mutations.

Materials and Methods

As of 22 January 2020, total of 994 mCRC patients were registered in K-MASTER project. Targeted sequencing was performed using three platforms which were composed of the K-MASTER cancer panel v1.1 and the SNUH FIRST Cancer Panel v3.01. If tumor tissue was not available, cell-free DNA was extracted and the targeted sequencing was performed by Axen Cancer Panel as a liquid biopsy.

Results

In 994 mCRC patients, we found 1,564 clinically meaningful pathogenic variants which mutated in 71 genes. Anti-EGFR therapy candidates were 467 patients (47.0%) and BRAF V600E mutation (n=47, 4.7%), deficient mismatch repair/microsatellite instability–high (n=15, 1.5%), HER2 amplifications (n=10, 1.0%) could be incorporated with recently approved drugs. The patients with high tumor mutation burden (n=101, 12.7%) and DNA damaging response and repair defect pathway alteration (n=42, 4.2%) could be enrolled clinical trials with immune checkpoint inhibitors. There were more colorectal cancer molecular alterations such as PIK3CA, KRAS G12C, atypical BRAF, and HER2 mutations and even rarer but actionable genes that approved or ongoing clinical trials in other solid tumors.

Conclusion

K-MASTER project provides an intriguing background to investigate new clinical trials with biomarkers and give therapeutic opportunity for mCRC patients.