Tumor Size Matters-Understanding Concomitant Tumor Immunity in the Context of Hypofractionated Radiotherapy with Immunotherapy.

The purpose of this study was to determine the dynamic contributions of different immune cell subsets to primary and abscopal tumor regression after hypofractionated radiation therapy (hRT) and the impact of anti-PD-1 therapy. A bilateral syngeneic FSA1 fibrosarcoma model was used in immunocompetent C3H mice, with delayed inoculation to mimic primary and microscopic disease. The effect of tumor burden on intratumoral and splenic immune cell content was delineated as a prelude to hRT on macroscopic T1 tumors with 3 fractions of 8 Gy while microscopic T2 tumors were left untreated. This was performed with and without systemic anti-PD-1. Immune profiles within T1 and T2 tumors and in spleen changed drastically with tumor burden in untreated mice with infiltrating CD4+ content declining, while the proportion of CD4+ Tregs rose. Myeloid cell representation escalated in larger tumors, resulting in major decreases in the lymphoid:myeloid ratios. In general, activation of Tregs and myeloid-derived suppressor cells allow immunogenic tumors to grow, although their relative contributions change with time. The evidence suggests that primary T1 tumors self-regulate their immune content depending on their size and this can influence the lymphoid compartment of T2 tumors, especially with respect to Tregs. Tumor burden is a major confounding factor in immune analysis that has to be taken into consideration in experimental models and in the clinic. hRT caused complete local regression of primary tumors, which was accompanied by heavy infiltration of CD8+ T cells activated to express IFN-γ and PD-1; while certain myeloid populations diminished. In spite of this active infiltrate, primary hRT failed to generate the systemic conditions required to cause abscopal regression of unirradiated microscopic tumors unless PD-1 blockade, which on its own was ineffective, was added to the RT regimen. The combination further increased local and systemically activated CD8+ T cells, but few other changes. This study emphasizes the subtle interplay between the immune system and tumors as they grow and how difficult it is for local RT, which can generate a local immune response that may help with primary tumor regression, to overcome the systemic barriers that are generated so as to effect immune regression of even small abscopal lesions

Adaptation of the Tumor Antigen Presentation Machinery to Ionizing Radiation.

Ionizing radiation (IR) can reprogram proteasome structure and function in cells and tissues. In this article, we show that IR can promote immunoproteasome synthesis with important implications for Ag processing and presentation and tumor immunity. Irradiation of a murine fibrosarcoma (FSA) induced dose-dependent de novo biosynthesis of the immunoproteasome subunits LMP7, LMP2, and Mecl-1, in concert with other changes in the Ag-presentation machinery (APM) essential for CD8+ T cell-mediated immunity, including enhanced expression of MHC class I (MHC-I), β2-microglobulin, transporters associated with Ag processing molecules, and their key transcriptional activator NOD-like receptor family CARD domain containing 5. In contrast, in another less immunogenic, murine fibrosarcoma (NFSA), LMP7 transcripts and expression of components of the immunoproteasome and the APM were muted after IR, which affected MHC-I expression and CD8+ T lymphocyte infiltration into NFSA tumors in vivo. Introduction of LMP7 into NFSA largely corrected these deficiencies, enhancing MHC-I expression and in vivo tumor immunogenicity. The immune adaptation in response to IR mirrored many aspects of the response to IFN-γ in coordinating the transcriptional MHC-I program, albeit with notable differences. Further investigations showed divergent upstream pathways in that, unlike IFN-γ, IR failed to activate STAT-1 in either FSA or NFSA cells while heavily relying on NF-κB activation. The IR-induced shift toward immunoproteasome production within a tumor indicates that proteasomal reprogramming is part of an integrated and dynamic tumor-host response that is specific to the stressor and the tumor and therefore is of clinical relevance for radiation oncology

A novel multiplex assay combining autoantibodies plus PSA has potential implications for classification of prostate cancer from non-malignant cases

<p>Abstract</p> <p>Background</p> <p>The lack of sufficient specificity and sensitivity among conventional cancer biomarkers, such as prostate specific antigen (PSA) for prostate cancer has been widely recognized after several decades of clinical implications. Autoantibodies (autoAb) among others are being extensively investigated as potential substitute markers, but remain elusive. One major obstacle is the lack of a sensitive and multiplex approach for quantifying autoAb against a large panel of clinically relevant tumor-associated antigens (TAA).</p> <p>Methods</p> <p>To circumvent preparation of phage lysates and purification of recombinant proteins, we identified B cell epitopes from a number of previously defined prostate cancer-associated antigens (PCAA). Peptide epitopes from cancer/testis antigen NY-ESO-1, XAGE-1b, SSX-2,4, as well as prostate cancer overexpressed antigen AMACR, p90 autoantigen, and LEDGF were then conjugated with seroMAP microspheres to allow multiplex measurement of autoAb present in serum samples. Moreover, simultaneous quantification of autoAb plus total PSA was achieved in one reaction, and termed the "A+PSA" assay.</p> <p>Results</p> <p>Peptide epitopes from the above 6 PCAA were identified and confirmed that autoAb against these peptide epitopes reacted specifically with the full-length protein. A pilot study was conducted with the A+PSA assay using pre-surgery sera from 131 biopsy-confirmed prostate cancer patients and 121 benign prostatic hyperplasia and/or prostatitis patients. A logistic regression-based A+PSA index was found to enhance sensitivities and specificities over PSA alone in distinguishing prostate cancer from nonmalignant cases. The A+PSA index also reduced false positive rate and improved the area under a receiver operating characteristic curve.</p> <p>Conclusions</p> <p>The A+PSA assay represents a novel platform that integrates autoAb signatures with a conventional cancer biomarker, which may aid in the diagnosis and prognosis of prostate cancer and others.</p

Tumour-intrinsic resistance to immune checkpoint blockade

'Immune checkpoint blockade' for cancer describes the use of therapeutic antibodies that disrupt negative immune regulatory checkpoints and unleash pre-existing antitumour immune responses. Antibodies targeting the checkpoint molecules cytotoxic T lymphocyte antigen 4 (CTLA4), programmed cell death 1 (PD1) and PD1 ligand 1 (PD-L1) have had early success in the clinic, which has led to approval by the US Food and Drug Administration of multiple agents in several cancer types. Yet, clinicians still have very limited tools to discriminate a priori patients who will and will not respond to treatment. This has fuelled a wave of research into the molecular mechanisms of tumour-intrinsic resistance to immune checkpoint blockade, leading to the rediscovery of biological processes critical to antitumour immunity, namely interferon signalling and antigen presentation. Other efforts have shed light on the immunological implications of canonical cancer signalling pathways, such as WNT-β-catenin signalling, cell cycle regulatory signalling, mitogen-activated protein kinase signalling and pathways activated by loss of the tumour suppressor phosphoinositide phosphatase PTEN. Here we review each of these molecular mechanisms of resistance and explore ongoing approaches to overcome resistance to immune checkpoint blockade and expand the spectrum of patients who can benefit from immune checkpoint blockade

Antigen Presentation Keeps Trending in Immunotherapy Resistance

Through a gain-of-function kinome screen, MEX3B was identified as a mediator of resistance to T-cell immunotherapy not previously identified using CRISPR-based screens. MEX3B is a posttranscriptional regulator of HLA-A, validating the critical role of tumor-intrinsic antigen presentation in T-cell immunotherapy and indicating a new putative molecular target. Clin Cancer Res; 24(14); 3239-41. ©2018 AACRSee related article by Huang et al., p. 3366

Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles.

Elucidating antiviral CD8 T lymphocyte responses to SARS-CoV-2 may shed light on the heterogeneity of clinical outcomes and inform vaccine or therapeutic approaches. To facilitate the evaluation of antiviral CD8 T cell responses to SARS-CoV-2, we generated a publicly accessible database of epitopes predicted to bind any class I HLA protein across the entire SARS-CoV-2 proteome. While a subset of epitopes from earlier betacoronaviruses, such as SARS-CoV (SARS), have been validated experimentally, validation systems are often biased toward specific HLA haplotypes (notably HLA-A*02:01) that only account for a fraction of the haplotypes of individuals affected by the SARS-CoV-2 pandemic. To enable evaluation of epitopes across individuals with a variety of HLA haplotypes, we computed the predicted binding affinities between 9-mer peptides derived from the annotated SARS-CoV-2 peptidome across 9,360 MHC class I HLA-A, -B, and -C alleles. There were 6,748 unique combinations of peptides and HLA alleles (pMHCs) with a predicted binding affinity of less than 500nM, including 1,103 unique peptides and 1,022 HLA alleles, spanning 11 annotated superfamilies. These peptides were derived from all 11 proteins spanning the SARS-CoV-2 peptidome, including peptides that have previously been validated experimentally. We also show evidence that these previously validated epitopes may be relevant in other HLA contexts. This complete dataset is available publicly: gs://pici-covid19-data-resources/mhci/peptide_predictions

Prediction of SARS-CoV-2 epitopes across 9360 HLA class I alleles.

Elucidating antiviral CD8 T lymphocyte responses to SARS-CoV-2 may shed light on the heterogeneity of clinical outcomes and inform vaccine or therapeutic approaches. To facilitate the evaluation of antiviral CD8 T cell responses to SARS-CoV-2, we generated a publicly accessible database of epitopes predicted to bind any class I HLA protein across the entire SARS-CoV-2 proteome. While a subset of epitopes from earlier betacoronaviruses, such as SARS-CoV (SARS), have been validated experimentally, validation systems are often biased toward specific HLA haplotypes (notably HLA-A*02:01) that only account for a fraction of the haplotypes of individuals affected by the SARS-CoV-2 pandemic. To enable evaluation of epitopes across individuals with a variety of HLA haplotypes, we computed the predicted binding affinities between 9-mer peptides derived from the annotated SARS-CoV-2 peptidome across 9,360 MHC class I HLA-A, -B, and -C alleles. There were 6,748 unique combinations of peptides and HLA alleles (pMHCs) with a predicted binding affinity of less than 500nM, including 1,103 unique peptides and 1,022 HLA alleles, spanning 11 annotated superfamilies. These peptides were derived from all 11 proteins spanning the SARS-CoV-2 peptidome, including peptides that have previously been validated experimentally. We also show evidence that these previously validated epitopes may be relevant in other HLA contexts. This complete dataset is available publicly: gs://pici-covid19-data-resources/mhci/peptide_predictions