Considering molecular alterations as pan-cancer tissue-agnostic targets

If it is a solid tumor target, then it may be a hematologic cancer target: Bridging the great divide

Tumor-agnostic US Food and Drug Administration approvals are transforming oncology. They include larotrectinib/entrectinib/repotrectinib (NTRK fusions), selpercatinib (RET fusions), dabrafenib/trametinib (BRAFV600E mutations), pembrolizumab/dostarlimab (microsatellite instability), pembrolizumab (high tumor mutational burden), and trastuzumab deruxtecan (HER2 3+ expression) (all solid cancers). Pemigatinib is approved for FGFR1-rearranged myeloid/lymphoid neoplasms. The genomically driven tissue-agnostic approach has a strong biological rationale (cancer is a disease of the genome), yields remarkably high response rates, and provides drug access to patients with an unmet need (rare/ultra-rare malignancies). Despite the solid tumor focus, both solid and hematologic cancers can harbor identical driver molecular abnormalities and respond to cognate therapies. For example, BRAFV600E and IDH1/2 mutations; ALK, FGFR, and NTRK fusions; PD-L1 amplification; and CD70 antigens are druggable in both solid and blood malignancies by gene-/immune-targeted therapies/chimeric antigen receptor T cells. Future biomarker-based tissue-agnostic basket studies/approvals should bridge the great divide and include both solid and hematologic cancers.

Identification of a central network hub of key prognostic genes based on correlation between transcriptomics and survival in patients with metastatic solid tumors

Background

Dysregulated pathways in cancer may be hub addicted. Identifying these dysregulated networks for targeting might lead to novel therapeutic options.

Objective

Considering the hypothesis that central hubs are associated with increased lethality, identifying key hub targets within central networks could lead to the development of novel drugs with improved efficacy in advanced metastatic solid tumors.

Design

Exploring transcriptomic data (22,000 gene products) from the WINTHER trial (N = 101 patients with various metastatic cancers), in which both tumor and normal organ-matched tissue were available.

Methods

A retrospective in silico analysis of all genes in the transcriptome was conducted to identify genes different in expression between tumor and normal tissues (paired t-test) and to determine their association with survival outcomes using survival analysis (Cox proportional hazard regression algorithm). Based on the biological relevance of the identified genes, hub targets of interest within central networks were then pinpointed. Patients were grouped based on the expression level of these genes (K-mean clustering), and the association of these groups with survival was examined (Cox proportional hazard regression algorithm, Forest plot, and Kaplan-Meier plot).

Results

We identified four key central hub genes-PLOD3, ARHGAP11A, RNF216, and CDCA8, for which high expression in tumor tissue compared to analogous normal tissue had the most significant correlation with worse outcomes. The correlation was independent of tumor or treatment type. The combination of the four genes showed the highest significance and correlation with the poorer outcome: overall survival (hazard ratio (95% confidence interval (CI)) = 10.5 (3.43-31.9) p = 9.12E-07 log-rank test in a Cox proportional hazard regression model). Findings were validated in independent cohorts.

Conclusion

The expression of PLOD3, ARHGAP11A, RNF216, and CDCA8 constitute, when combined, a prognostic tool, agnostic of tumor type and previous treatments. These genes represent potential targets for intercepting central hub networks in various cancers, offering avenues for novel therapeutic interventions.

If it's a target, it's a pan-cancer target: Tissue is not the issue

Cancer is traditionally diagnosed and treated on the basis of its organ of origin (e.g., lung or colon cancer). However, organ-of-origin diagnostics does not reveal the underlying oncogenic drivers. Fortunately, molecular diagnostics have advanced at a breathtaking pace, and it is increasingly apparent that cancer is a disease of the genome. Hence, we now have multiple genomic biomarker-based, tissue-agnostic Food and Drug Administration approvals for both gene- and immune-targeted therapies (larotrectinib/entrectinib, for NTRK fusions; selpercatinib, RET fusions; dabrafenib plus trametinib, BRAFV600E mutations; pembrolizumab/dostarlimab, microsatellite instability; and pembrolizumab for high tumor mutational burden; pemigatinib is also approved for FGFR1-rearranged myeloid/lymphoid neoplasms). There are emerging targets as well, including but not limited to ALK, BRCA and/or homologous repair deficiency, ERBB2 (HER2), IDH1/2, KIT, KRASG12C, NRG1, and VHL. Many tissue-agnostic approvals center on rare/ultra-rare biomarkers (often < 1 % of cancers), necessitating screening hundreds of tumors to find a single one harboring the cognate molecular alteration. Approval has generally been based on small single-arm studies (<30-100 patients) with high response rates (>30 % to > 75 %) of remarkable durability. Because of biomarker rarity, single-gene testing is not practical; next generation sequencing of hundreds of genes must be performed to obtain timely answers. Resistance to biomarker-driven therapeutics is often due to secondary mutations or co-driver gene defects; studies are now addressing the need for customized drug combinations matched to the complex molecular alteration portfolio in each tumor. Future investigation should expand tissue-agnostic therapeutics to encompass both hematologic and solid malignancies and include biomarkers beyond those that are DNA-based.