CAV2 promotes the invasion and metastasis of head and neck squamous cell carcinomas by regulating S100 proteins

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.

The dynamic role of immune checkpoint molecules in diagnosis, prognosis, and treatment of head and neck cancers

Head and neck cancer (HNC) is the sixth most common cancer type, accounting for approximately 277,597 deaths worldwide. Recently, the Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) agents targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) as a treatment regimen for head and neck squamous cell carcinomas (HNSCC). Studies have reported the role of immune checkpoint inhibitors as targeted therapeutic regimens that unleash the immune response against HNSCC tumors. However, the overall response rates to immunotherapy vary between 14-32% in recurrent or metastatic HNSCC, with clinical response and treatment success being unpredictable. Keeping this perspective in mind, it is imperative to understand the role of T cells, natural killer cells, and antigen-presenting cells in modulating the immune response to immunotherapy. In lieu of this, these immune molecules could serve as prognostic and predictive biomarkers to facilitate longitudinal monitoring and understanding of treatment dynamics. These immune biomarkers could pave the path for personalized monitoring and management of HNSCC. In this review, we aim to provide updated immunological insight on the mechanism of action, expression, and the clinical application of immune cells' stimulatory and inhibitory molecules as prognostic and predictive biomarkers in HNC. The review is focused mainly on CD27 and CD137 (members of the TNF-receptor superfamily), natural killer group 2 member D (NKG2D), tumor necrosis factor receptor superfamily member 4 (TNFRSF4 or OX40), S100 proteins, PD-1, PD-L1, PD-L2, T cell immunoglobulin and mucin domain 3 (TIM-3), cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), lymphocyte-activation gene 3 (LAG-3), indoleamine-pyrrole 2,3-dioxygenase (IDO), B and T lymphocyte attenuator (BTLA). It also highlights the importance of T, natural killer, and antigen-presenting cells as robust biomarker tools for understanding immune checkpoint inhibitor-based treatment dynamics. Though a comprehensive review, all aspects of the immune molecules could not be covered as they were beyond the scope of the review; Further review articles can cover other aspects to bridge the knowledge gap.

The genomic signature of resistance to platinum-containing neoadjuvant therapy based on single-cell data

BACKGROUND

Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT.

METHODS

Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro.

RESULTS

485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin.

CONCLUSIONS

NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.