Integrated genomic and transcriptomic analysis revealed mutation patterns of de-differentiated liposarcoma and leiomyosarcoma

PD-1 blockade plus COX inhibitors in dMMR metastatic colorectal cancer: Clinical, genomic, and immunologic analyses from the PCOX trial

BACKGROUND

Approximately 20% of patients with DNA mismatch repair deficiency (dMMR) metastatic colorectal cancer do not respond to anti-programmed death-1 (PD-1) ligand therapy, and baseline biomarkers of response are lacking.

METHODS

We conducted a phase 2 study to evaluate the efficacy of cyclooxygenase (COX) inhibitors in combination with anti-PD-1 therapy in patients with dMMR metastatic colorectal cancer. The primary endpoint was objective response rate. The secondary endpoints included progression-free survival (PFS), overall survival (OS), disease control rate, duration of response, and safety.

FINDINGS

A total of 30 patients were enrolled, and the objective response rate was 73.3%, meeting the predefined endpoint of 68%. The median PFS and median OS were not reached at a median follow-up period of 50.8 months. Disease control was achieved in 28 patients (93.3%). The median duration of response was not reached. The combination was well tolerated. Multiomics analysis revealed that the antigen processing and presentation pathway was positively associated with treatment response and PFS. Higher TAPBP expression was predictive of better PFS (log-rank p = 0.003), and this prognostic significance was confirmed in an immunotherapy validation cohort.

CONCLUSIONS

Thus, COX inhibitors combined with PD-1 blockade may be effective and safe treatment options for patients with dMMR metastatic colorectal cancer, and TAPBP may serve as a biomarker for immune checkpoint inhibitor therapy (this study was registered at ClinicalTrials.gov: NCT03638297).

FUNDING

Funded by the National Natural Science Foundation of China (81974369) and the program of Guangdong Provincial Clinical Research Center for Digestive Diseases (2020B1111170004).

Molecular Heterogeneity in Leiomyosarcoma and Implications for Personalised Medicine

OPINION STATEMENT

Leiomyosarcoma (LMS) is one of the more common subtypes of soft tissue sarcomas (STS), accounting for about 20% of cases. Differences in anatomical location, risk of recurrence and histomorphological variants contribute to the substantial clinical heterogeneity in survival outcomes and therapy responses observed in patients. There is therefore a need to move away from the current one-size-fits-all treatment approach towards a personalised strategy tailored for individual patients. Over the past decade, tissue profiling studies have revealed key genomic features and an additional layer of molecular heterogeneity among patients, with potential utility for optimal risk stratification and biomarker-matched therapies. Furthermore, recent studies investigating intratumour heterogeneity and tumour evolution patterns in LMS suggest some key features that may need to be taken into consideration when designing treatment strategies and clinical trials. Moving forward, national and international collaborative efforts to aggregate expertise, data, resources and tools are needed to achieve a step change in improving patient survival outcomes in this disease of unmet need.

Targeting the Molecular and Immunologic Features of Leiomyosarcoma

Leiomyosarcoma (LMS) is a rare, aggressive mesenchymal tumor with smooth muscle differentiation. LMS is one of the most common histologic subtypes of soft tissue sarcoma; it most frequently occurs in the extremities, retroperitoneum, or uterus. LMS often demonstrates aggressive tumor biology, with a higher risk of developing distant metastatic disease than most sarcoma histologic types. The prognosis is poor, particularly in patients with uterine disease, and there is a need for the development of more effective therapies. Genetically, LMS is karyotypically complex and characterized by a low tumor mutational burden, with frequent alterations in TP53, RB1, PTEN, and DNA damage response pathways that may contribute to resistance against immune-checkpoint blockade monotherapy. The LMS immune microenvironment is highly infiltrated with tumor-associated macrophages and tumor-infiltrating lymphocytes, which may represent promising biomarkers. This review provides an overview of the clinical and pathologic behavior of both soft tissue and uterine LMS and summarizes the genomic and immune characteristics of these tumors and how they may provide opportunities for the development of biomarker-based immune therapies.

Targeting the MDM2-p53 pathway in dedifferentiated liposarcoma

Dedifferentiated liposarcoma (DDLPS) is an aggressive adipogenic cancer with poor prognosis. DDLPS tumors are only modestly sensitive to chemotherapy and radiation, and there is a need for more effective therapies. Genetically, DDLPS is characterized by a low tumor mutational burden and frequent chromosomal structural abnormalities including amplification of the 12q13-15 chromosomal region and the MDM2 gene, which are defining features of DDLPS. The MDM2 protein is an E3 ubiquitin ligase that targets the tumor suppressor, p53, for proteasomal degradation. MDM2 amplification or overexpression in human malignancies is associated with cell-cycle progression and worse prognosis. The MDM2-p53 interaction has thus garnered interest as a therapeutic target for DDLPS and other malignancies. MDM2 binds p53 via a hydrophobic protein interaction that is easily accessible with synthetic analogues. Multiple agents have been developed, including Nutlins such as RG7112 and small molecular inhibitors including SAR405838 and HDM201. Preclinical in vitro and animal models have shown promising results with MDM2 inhibition, resulting in robust p53 reactivation and cancer cell death. However, multiple early-phase clinical trials have failed to show a benefit with MDM2 pathway inhibition for DDLPS. Mechanisms of resistance are being elucidated, and novel inhibitors and combination therapies are currently under investigation. This review provides an overview of these strategies for targeting MDM2 in DDLPS.

Integrative genomic analysis of drug resistance in MET exon 14 skipping lung cancer using patient-derived xenograft models

Background

Non-small cell lung cancer (NSCLC) driven by MET exon 14 skipping (METex14) occurs in 3-4% of NSCLC cases and defines a subset of patients with distinct characteristics. While MET targeted therapy has led to strong clinical results in METex14 patients, acquired drug resistance seemed to be unavoidable during treatment. Limited information is available regarding acquired resistance during MET targeted therapy, nor has there been any report on such patient-derived xenografts (PDXs) model facilitating the research.

Methods

We describe a patient case harboring METex14 who exhibited drug resistance after treatment with crizotinib. Subcutaneous xenografts were generated from pretreatment and post-resistance patient specimens. PDX mice were then treated with MET inhibitors (crizotinib and tepotinib) and EGFR-MET bispecific antibodies (EMB-01 and amivantamab) to evaluate their drug response in vivo. DNA and RNA sequencing analysis was performed on patient tumor specimens and matching xenografts.

Results

PDXs preserved most of the histological and molecular profiles of the parental tumors. Drug resistance to MET targeted therapy was confirmed in PDX models through in vivo drug analysis. Newly acquired MET D1228H mutations and EGFR amplificated were detected in patient-resistant tumor specimens. Although the mutations were not detected in the PDX, EGFR overexpression was observed in RNA sequencing analysis indicating possible off-target resistance through the EGFR bypass signaling pathway. As expected, EGFR-MET bispecific antibodies overcome drug resistant in the PDX model.

Conclusions

We detected a novel MET splice site deletion mutation that could lead to METex14. We also established and characterized a pair of METex14 NSCLC PDXs, including the first crizotinib resistant METex14 PDX. And dual inhibition of MET and EGFR might be a therapeutic strategy for EGFR-driven drug resistance METex14 lung cancer.

On the Relevance of Soft Tissue Sarcomas Metabolic Landscape Mapping

Soft tissue sarcomas (STS) prognosis is disappointing, with current treatment strategies being based on a "fit for all" principle and not taking distinct sarcoma subtypes specificities and genetic/metabolic differences into consideration. The paucity of precision therapies in STS reflects the shortage of studies that seek to decipher the sarcomagenesis mechanisms. There is an urge to improve STS diagnosis precision, refine STS classification criteria, and increase the capability of identifying STS prognostic biomarkers. Single-omics and multi-omics studies may play a key role on decodifying sarcomagenesis. Metabolomics provides a singular insight, either as a single-omics approach or as part of a multi-omics strategy, into the metabolic adaptations that support sarcomagenesis. Although STS metabolome is scarcely characterized, untargeted and targeted metabolomics approaches employing different data acquisition methods such as mass spectrometry (MS), MS imaging, and nuclear magnetic resonance (NMR) spectroscopy provided important information, warranting further studies. New chromatographic, MS, NMR-based, and flow cytometry-based methods will offer opportunities to therapeutically target metabolic pathways and to monitorize the response to such metabolic targeting therapies. Here we provide a comprehensive review of STS omics applications, comprising a detailed analysis of studies focused on the metabolic landscape of these tumors.

Application of Multi-Omics Approach in Sarcomas: A Tool for Studying Mechanism, Biomarkers, and Therapeutic Targets

Sarcomas are rare, heterogeneous mesenchymal neoplasms with various subtypes, each exhibiting unique genetic characteristics. Although studies have been conducted to improve the treatment for sarcomas, the specific development from normal somatic cells to sarcoma cells is still unclear and needs further research. The diagnosis of sarcomas depends heavily on the pathological examination, which is yet a difficult work and requires expert analysis. Advanced treatment like precise medicine optimizes the efficacy of treatment and the prognosis of sarcoma patients, yet, in sarcomas, more studies should be done to put such methods in clinical practice. The revolution of advanced technology has pushed the multi-omics approach to the front, and more could be learnt in sarcomas with such methods. Multi-omics combines the character of each omics techniques, analyzes the mechanism of tumor cells from different levels, which makes up for the shortage of single-omics, and gives us an integrated picture of bioactivities inside tumor cells. Multi-omics research of sarcomas has reached appreciable progress in recent years, leading to a better understanding of the mutation, proliferation, and metastasis of sarcomas. With the help of multi-omics approach, novel biomarkers were found, with promising effects in improving the process of diagnosis, prognosis anticipation, and treatment decision. By analyzing large amounts of biological features, subtype clustering could be done in a better precision, which may be useful in the clinical procedure. In this review, we summarized recent discoveries using multi-omics approach in sarcomas, discussed their merits and challenges, and concluded with future perspectives of the sarcoma research.

Clinicopathological Significance of ATRX Expression in Nasopharyngeal Carcinoma Patients: A Retrospective Study

Background: Nasopharyngeal carcinoma (NPC) is the most common head and neck squamous cell carcinoma in south China. Radiation technology improves the local control rates in early NPC. However, the distant metastases are still the main cause of treatment failure. Thus, to find biomarkers for prognosis will help to enhance the survival of NPC. ATRX is a chromatin remodeling protein localized in the nucleus. Deletion or mutation of ATRX gene has been demonstrated in a variety of malignancies. However, the significance of ATRX expression in the prognosis of NPC remains unclear.

Methods: Tumor tissues from 227 NPC patients diagnosed in the Second Xiangya Hospital of Central South University from 2011 to 2016 were selected. Immunohistochemistry was used to detect the ATRX expression level of the tumor tissue. Chi-square test was used to analyze the relationship between ATRX expression and clinical characteristics such as age, sex, T stage, N stage and clinical stage. Kaplan-Meier method was used for survival analysis, and log-rank was used to compare the difference in survival rate.

Results: There were 53 patients with negative ATRX expression, accounting for 24.2% of the total group. ATRX expression was not significantly associated with age, sex, N stage, clinical stage, and progression-free survival (PFS) (P>0.05). However, patients with negative ATRX expression had earlier T staging (P=0.045) and a higher 5-year overall survival (84.9% vs 66.9%, P=0.022).

Conclusions: Loss of ATRX expression may contribute to better prognosis in patients with NPC.