Mechanism of ERBB2 gene overexpression by the formation of super-enhancer with genomic structural abnormalities in lung adenocarcinoma without clinically actionable genetic alterations.

BACKGROUND: In an extensive genomic analysis of lung adenocarcinomas (LUADs), driver mutations have been recognized as potential targets for molecular therapy. However, there remain cases where target genes are not identified. Super-enhancers and structural variants are frequently identified in several hundred loci per case. Despite this, most cancer research has approached the analysis of these data sets separately, without merging and comparing the data, and there are no examples of integrated analysis in LUAD. METHODS: We performed an integrated analysis of super-enhancers and structural variants in a cohort of 174 LUAD cases that lacked clinically actionable genetic alterations. To achieve this, we conducted both WGS and H3K27Ac ChIP-seq analyses using samples with driver gene mutations and those without, allowing for a comprehensive investigation of the potential roles of super-enhancer in LUAD cases. RESULTS: We demonstrate that most genes situated in these overlapped regions were associated with known and previously unknown driver genes and aberrant expression resulting from the formation of super-enhancers accompanied by genomic structural abnormalities. Hi-C and long-read sequencing data further corroborated this insight. When we employed CRISPR-Cas9 to induce structural abnormalities that mimicked cases with outlier ERBB2 gene expression, we observed an elevation in ERBB2 expression. These abnormalities are associated with a higher risk of recurrence after surgery, irrespective of the presence or absence of driver mutations. CONCLUSIONS: Our findings suggest that aberrant gene expression linked to structural polymorphisms can significantly impact personalized cancer treatment by facilitating the identification of driver mutations and prognostic factors, contributing to a more comprehensive understanding of LUAD pathogenesis.

Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies.

The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics-driven precision oncology has thus far benefited only 10%-20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics-based approaches, proteomics-based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker-drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse-phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost-effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics-driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

Establishment and characterization of multiple patient-derived organoids from a case of advanced endometrial cancer.

Patient-derived organoids (PDOs) retain the original tumor's characteristics to a large degree and allow direct evaluation of the drug sensitivity, thereby emerging as a valuable resource for both basic and preclinical researches. Whereas most past studies stereotypically adopted a single PDO as an avatar of the patient, it remains to be investigated whether this assumption can be justified even for the tumor with spatial diversity. To address this issue, we established and characterized multiple PDOs originating from various sites of a patient with advanced uterine carcinosarcoma (UCS). Specifically, cancer cells were separately sampled from three sites; resected UCS tumor tissue, the peritoneal lavage fluid, and an intra-uterine brushing of the tumor. The three derived PDOs were morphologically undistinguishable, displaying typical carcinoma organoids-like appearance, but two of them proliferated at a faster rate. The primary tumor harbored mutations in TP53 and STK11 along with amplifications in CCNE1, ERBB2, and KRAS. These two mutations and the CCNE1 amplification were detected in all PDOs, while either KRAS or ERBB2 amplification was selectively observed in each PDO in a mutually exclusive manner. Observed intra-tumor heterogeneity in HER2 expression was differentially reproduced in the PDOs, which mirrored each PDO's sensitivity to HER2 inhibitors. Inter-PDO heterogeneity was also evident in sensitivity to standard cytotoxic agents. Lastly, a drug screening identified four candidate reagents commonly effective to all PDOs. Collectively, we showed that multiple PDOs could help reproduce the spatial diversity of a tumor and serve as a valuable resource in UCS research in many respects.