EZR-ROS1 fusion renal cell carcinoma mimicking urothelial carcinoma: report of a previously undescribed gene fusion in renal cell carcinoma

Clinical Utility and Benefits of Comprehensive Genomic Profiling in Cancer

BACKGROUND

Comprehensive genomic profiling (CGP) with next-generation sequencing detects genetic alterations of hundreds of genes simultaneously and multiple molecular biomarkers with one test. In the personalized medicine era, CGP is increasingly used for cancer diagnosis, treatment selection, and prognosis prediction.

CONTENT

In this review, we summarize the benefits of CGP, clinical utility of CGP, and challenges of setting up CGP in the clinical laboratories. Besides the genetic alterations identified in the cancer-related genes, other biomarkers such as tumor mutational burden, microsatellite instability, and homologous recombination deficiency are critical for initiating targeted therapy. Compared with conventional tests, CGP uses less specimen and shortens the turnaround time if multiple biomarkers need to be tested. RNA fusion assay and liquid biopsy are helpful additions to DNA-based CGP by detecting fusions/splicing variants and complementing tissue-based CGP findings, respectively.

SUMMARY

Many previous hurdles for implementing CGP in the clinical laboratories have been gradually alleviated such as the decrease in sequencing cost, availability of both open-source and commercial bioinformatics tools, and improved reimbursement. These changes have helped to make CGP available to a greater population of cancer patients for improving characterization of their tumors and expanding their eligibility for clinical trials. Additionally, sequencing results of the hundreds of genes on CGP panels could be further analyzed to better understand the biology of various cancers and identify new biomarkers.

Molecular differences in renal cell carcinoma between males and females

PURPOSE

The disparity in renal cell carcinoma (RCC) risk and treatment outcome between males and females is well documented, but the underlying molecular mechanisms remain poorly elucidated.

METHODS

We performed a narrative review synthesizing contemporary evidence on sex-specific molecular differences in healthy kidney tissue and RCC.

RESULTS

In healthy kidney tissue, gene expression differs significantly between males and females, including autosomal and sex-chromosome-linked genes. The differences are most prominent for sex-chromosome-linked genes and attributable to Escape from X chromosome-linked inactivation and Y chromosome loss. The frequency distribution of RCC histologies varies between the sexes, particularly for papillary, chromophobe, and translocation RCC. In clear-cell and papillary RCC, sex-specific gene expressions are pronounced, and some of these genes are amenable to pharmacotherapy. However, for many, the impact on tumorigenesis remains poorly understood. In clear-cell RCC, molecular subtypes and gene expression pathways have distinct sex-specific trends, which also apply to the expression of genes implicated in tumor progression.

CONCLUSION

Current evidence suggests meaningful genomic differences between male and female RCC, highlighting the need for sex-specific RCC research and personalized sex-specific treatment approaches.

Detection of ROS1 gene fusions using next-generation sequencing for patients with malignancy in China

Objective: This study aimed to identify ROS1 fusion partners in Chinese patients with solid tumors. Methods: Next-generation sequencing (NGS) analysis was used to detect ROS1 rearrangement in 45,438 Chinese patients with solid tumors between 2015 and 2020, and the clinical characteristics and genetic features of gene fusion were evaluated. H&E staining of the excised tumor tissues was conducted. Samples with a tumor cell content ≥ 20% were included for subsequent DNA extraction and sequencing analysis. Results: A total of 92 patients with ROS1 rearrangements were identified using next-generation sequencing, and the most common histological type lung cancer. From the 92 ROS1 fusion cases, 24 ROS1 fusion partners had been identified, including 14 novel partners and 10 reported partners. Of these, CD74, EZR, SDC4, and TPM3 were the four most frequently occurring partners. Fourteen novel ROS1 fusion partners were detected in 16 patients, including DCBLD1-ROS1, FRK-ROS1, and VGLL2-ROS1. In many patients, the ROS1 breakpoint was located between exons 32 and 34. Conclusion: This study describes 14 novel ROS1 fusion partners based on the largest ROS1 fusion cohort, and the ROS1 breakpoint was mostly located between exons 32 and 34. Additionally, next-generation sequencing is an optional method for identifying novel ROS1 fusions.