Lung-MAP Next-Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400).

Introduction: Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, that is, by next-generation sequencing (NGS), is needed to identify potential targets. Lung Cancer Master Protocol Southwest Oncology Group S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic sub-studies.

Chemical genetic screens reveal defective lysosomal trafficking as synthetic lethal with NF1 loss.

Neurofibromatosis type 1, a genetic disorder caused by pathogenic germline variations in NF1, predisposes individuals to the development of tumors, including cutaneous and plexiform neurofibromas (CNs and PNs), optic gliomas, astrocytomas, juvenile myelomonocytic leukemia, high-grade gliomas and malignant peripheral nerve sheath tumors (MPNSTs), which are chemotherapy- and radiation-resistant sarcomas with poor survival. Loss of NF1 also occurs in sporadic tumors, such as glioblastoma (GBM), melanoma, breast, ovarian and lung cancers. We performed a high-throughput screen for compounds that were synthetic lethal with NF1 loss, which identified several leads, including the small molecule Y102.

Biomarker-Driven Personalized Immunoprevention: Toward More Efficient Clinical Trials?

In this secondary analysis of specimens from the CANTOS trial, the investigators find that patients with clonal hematopoiesis mutations, particularly in the TET2 gene, predict a benefit of decreased cancer risk with the administration of the anti-IL1β agent canakinumab. Despite small numbers and the need for prospective validation, the findings are exciting as they demonstrate the potential for personalized chemoprevention approaches. Such personalized approaches can potentially enhance the feasibility of cancer prevention trials.

Pragmaticism in Cancer Clinical Trials.

Clinical trials are essential for advancing oncology treatment strategies and have contributed significantly to the decline in cancer mortality rates over the past decades. Traditional explanatory trials, focused on establishing intervention efficacy in ideal settings, often lack generalizability and may not reflect real-world patient care scenarios. Furthermore, increasing complexity in cancer clinical trial design has led to challenges such as protocol deviations, slow enrollment leading to lengthened durations of trial, and escalating costs.