Longitudinal plasma proteomic profiling of patients with non-small cell lung cancer undergoing immune checkpoint blockade.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have revolutionized the cancer therapy landscape due to long-term benefits in patients with advanced metastatic disease. However, robust predictive biomarkers for response are still lacking and treatment resistance is not fully understood. METHODS: We profiled approximately 800 pre-treatment and on-treatment plasma proteins from 143 ICI-treated patients with non-small cell lung cancer (NSCLC) using ELISA-based arrays. Different clinical parameters were collected from the patients including specific mutations, smoking habits, and body mass index, among others. Machine learning algorithms were used to identify a predictive signature for response. Bioinformatics tools were used for the identification of patient subtypes and analysis of differentially expressed proteins and pathways in each response group. RESULTS: We identified a predictive signature for response to treatment comprizing two proteins (CXCL8 and CXCL10) and two clinical parameters (age and sex). Bioinformatic analysis of the proteomic profiles identified three distinct patient clusters that correlated with multiple parameters such as response, sex and TNM (tumors, nodes, and metastasis) staging. Patients who did not benefit from ICI therapy exhibited significantly higher plasma levels of several proteins on-treatment, and enrichment in neutrophil-related proteins. CONCLUSIONS: Our study reveals potential biomarkers in blood plasma for predicting response to ICI therapy in patients with NSCLC and sheds light on mechanisms underlying therapy resistance.

AUG sequences are required to sustain nonsense-codon-mediated suppression of splicing.

More than 90% of human genes are rich in intronic latent 5' splice sites whose utilization in pre-mRNA splicing would introduce in-frame stop codons into the resultant mRNAs. We have therefore hypothesized that suppression of splicing (SOS) at latent 5' splice sites regulates alternative 5' splice site selection in a way that prevents the production of toxic nonsense mRNAs and verified this idea by showing that the removal of such in-frame stop codons is sufficient to activate latent splicing. Splicing control by SOS requires recognition of the mRNA reading frame, presumably recognizing the start codon sequence. Here we show that AUG sequences are indeed essential for SOS. Although protein translation does not seem to be required for SOS, the first AUG is shown here to be necessary but not sufficient. We further show that latent splicing can be elicited upon treatment with pactamycin-a drug known to block translation by its ability to recognize an RNA fold-but not by treatment with other drugs that inhibit translation through other mechanisms. The effect of pactamycin on SOS is dependent neither on steady-state translation nor on the pioneer round of translation. This effect is found for both transfected and endogenous genes, indicating that SOS is a natural mechanism.

Circulating autoantibodies to LGALS3BP: a novel biomarker for cancer.

PURPOSE: Circulating autoantibodies have been extensively investigated as possible markers for early diagnosis of cancer. The present study was carried out to investigate whether anti-LGALS3BP IgG autoantibodies could be classified as a biomarker for malignant tumors. METHODS: An in-house developed enzyme-linked immunosorbent assay was used to detect autoantibodies to LGALS3BP in sera from 71 patients with various types of cancers and 54 healthy subjects matched by age and gender. RESULTS: Patients with cancer have significant higher circulating levels of anti-LGALS3BP antibodies as compared to control subjects (P < 0.001). The test has a sensitivity of 33% and a specificity of 98%. CONCLUSIONS: Anti-LGALS3BP IgG autoantibodies are a promising biomarker for malignant tumors and could play a role in the development of a multimarker assay for the early detection of cancer.

An Antibody-based Blood Test Utilizing a Panel of Biomarkers as a New Method for Improved Breast Cancer Diagnosis.

In order to develop a new tool for diagnosis of breast cancer based on autoantibodies against a panel of biomarkers, a clinical trial including blood samples from 507 subjects was conducted. All subjects showed a breast abnormality on exam or breast imaging and final biopsy pathology of either breast cancer patients or healthy controls. Using an enzyme-linked immunosorbent assay, the samples were tested for autoantibodies against a predetermined number of biomarkers in various models that were used to determine a diagnosis, which was compared to the clinical status. Our new assay achieved a sensitivity of 95.2% [CI = 92.8-96.8%] at a fixed specificity of 49.5%. Receiver-operator characteristic curve analysis showed an area under the curve of 80.1% [CI = 72.6-87.6%]. These results suggest that a blood test which is based on models comprising several autoantibodies to specific biomarkers may be a new and novel tool for improving the diagnostic evaluation of breast cancer.

Stop codons affect 5' splice site selection by surveillance of splicing.

Pre-mRNA splicing involves recognition of a consensus sequence at the 5' splice site (SS). However, only some of the many potential sites that conform to the consensus are true ones, whereas the majority remain silent and are not normally used for splicing. We noticed that in most cases the utilization of such a latent intronic 5' SS for splicing would introduce an in-frame stop codon into the resultant mRNA. This finding suggested a link between SS selection and maintenance of an ORF within the mRNA. Here we tested this idea by analyzing the splicing of pre-mRNAs in which in-frame stop codons upstream of a latent 5' SS were mutated. We found that splicing with the latent site is indeed activated by such mutations. Our findings predict the existence of a checking mechanism, as a component of the nuclear pre-mRNA splicing machine, to ensure the maintenance of an ORF. This notion is highly important for accurate gene expression, as perturbations that would lead to splicing at these latent sites are expected to introduce in-frame stop codons into the majority of mRNAs.