CTLA4 underexpression

Our study shows that CTLA-4 is a more important immune checkpoint regulator in breast carcinomas in comparison to PD-L1. Thus, anti-CTLA-4 immunotherapy might prove to be of immense help in the treatment of invasive ductal carcinoma breast showing overexpression of CTLA-4.

Importantly, nonresponder patients with high prediction score turned out to have high CTLA4 expression, which suggested that neoadjuvant CTLA4 combination therapy might be effective for these patients. Our data and analysis results provide valuable insights into developing biomarkers and strategies for treating LUAD patients using immune checkpoint inhibitors.

Our findings suggest that CTLA-4 blockage of Nalm-6 cells causes an increase in antitumour activity of NK cells against these cells. Our study also provides evidence for the potential of cancer immunotherapy treatment using blocking anti-CTLA-4 mAbs.

There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy. High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

Eight of 25 (32%) prolactinomas and 3 of 11 (27%) GH-adenomas had an H-score greater than 20, while no differences were seen for the other types. These novel data highlight the expression of an immune checkpoint such as CTLA4 on pituitary endocrine cells, a finding that could be exploited for therapeutical applications.

Furthermore, CTLA4 may influence breast cancer prognosis through antigen binding, immunoglobulin complexes, lymphocyte-mediated immunity, and cytokine-cytokine receptor interaction. These findings help us understand how CTLA4 plays a role in breast cancer and set the stage for more research.

Using enhanced CT images, the SVM radiomic model effectively predicts CTLA4 expression levels. As a result, this model offers strong prognostic insights for HNSCCs, guiding precise diagnosis, treatment, and assisting in clinical decision-making.

In summary, the current study demonstrated that the EVs derived from canine B cell lymphoma impaired the anti-tumor activity of CD8 + T-cells and manipulated the possible induction of regulatory CD8 + T-cells to fail the activation of host cellular immunity.

Priming the primary tumour with high-intensity (~ 60 bar) photoacoustic waves generated with nanosecond-pulsed lasers and light-to-pressure transducers improved the response of 4T1 tumours to PDT. Penetration-resistant tumours require a combination of approaches to respond to treatments: tumour priming to facilitate drug infiltration, PDT for a strong local effect and a change in immunogenicity, and immunotherapy for a systemic effect.

Neither the presence of TIL nor TLS was associated with improved clinical outcomes. The apparent discrimination in functional profiles of distinct immune niches, independent of the overall level of leukocytes, illustrates the importance of spatial profiling to deconvolute how the immune microenvironment can dictate a therapeutic response and to identify biomarkers in the context of immunomodulatory treatment.

Proteomics analysis identified apoptosis to be a major affected pathway and we found that Ctla4 ectopic-expressing mouse melanoma cells (B2905-Ctla4-ee) were significantly resistant to doxorubicin-induced apoptosis as compared to empty vector (EV) controls...Interestingly, we also found that CTLA4 translocated to mitochondria, where it downregulated oxidative phosphorylation and increased glycolysis. These findings lead us to hypothesize that CTLA4 plays a significant role in regulating apoptosis and mitochondrial metabolic functions, leading to the promotion of melanoma progression and metastasis.

Genetic and expression alterations identified by the BostonGene Tumor PortraitTM TestEvent type analyzed in targeted panelsEvent typeCohort (N patients)*% cohort with event or # biomarkersEvents, status, or subtypeYesSNV/IndelMG (21)10%FAT4 Y558_V590delinsCAfs*5 LOF mutation COL2A1 W1348Nfs*13 LOF mutationYesSNV/IndelMD (40)6%KMT2B R1779* LOF mutation KMT2C S143Vfs*3 LOF mutation PRKDC Y4046* LOF mutationYesGermlineMG (21)5%MUTYH rs36053993, germline, pathogenicYesGermlineMD (40)3%BTD rs13078881, germline, pathogenicYesCNAMG (21)43%IGF1R amplification +8 copies MGMT loss FANCA loss MCL1 amplification +10 copies MYOCD amplification +3 copies AKT2 amplification +8 copies AMACR amplification +6 copies YAP1 amplification +7 copies TRAF2 loss EZH2 amplification +2 copies HMGA2 amplification +100 copies FRS2 amplification +61 copies DDIT3 amplification +39 copiesYesCNAMD (40)27.5%ERK1 amplification +2 copies FOXO1 amplification +5 copies HMGA2 amplification +2, +8 copies KMT2C amplification +3 copies NCOR1 amplification +7 copies TERT amplification +6 copies TSPAN31 amplification +30 copies HSF1 lossYesFusionsMG (20)10%MDM2-CR1 MDM2-TXNDC12 AC090825.1-IGF1RYesFusionsMD (39)15%FUS-KIAA1549 KIAA1549-CREB3L2 HMGA2-LRRC37A3 NAB2-STAT6 PPP1R12A-PAWR RB1-ZAR1LNoTMB**MG+MD (61)8%35.67 mut/Mb (Desmoid fibromatosis) 8.48 mut/Mb (Cutaneous angiosarcoma) 8.9 mut/Mb (Sarcoma, NOS) 16.1 mut/Mb (Skin Angiosarcoma) 18.8 mut/Mb (Undifferentiated pleomorphic sarcoma)NoMSI statusMG+MD (61)100%StableNoHLA loss of heterozygosityMG+MD (61)11%HLA-I LOH (Leiomyosarcoma (N=1), Ewing Sarcoma (N=1)) HLA-A (Dedifferentiated liposarcoma (N=1)) HLA-I (Chondrosarcoma (N=3), High-grade sarcoma (N=1))NoTargetable surface molecule overexpressionMG+MD (59)81%CTLA4, EGFR, ERBB2, MAGEA3, PD1, PDL1, TIM3, TROP, ERBB2, FOLR1, NECTIN4, ROR1, TROP2NoMolecular Functional PortraitTM typeMG+MD (59)32%FibroticNoMolecular Functional PortraitTM typeMG+MD (59)17%Immune DesertNoMolecular Functional PortraitTM typeMG+MD (59)24%Immune-Enriched, FibroticNoMolecular Functional PortraitTM typeMG+MD (59)27%Immune-Enriched, Non-fibroticNoMHC deficiencyMG+MD (59)3%MHC class I/II deficiencyNoMHC deficiencyMG+MD (59)3%MHC class II deficiencyNoFDA label biomarkersMG+MD (59)7 biomarkers- Desmoid fibromatosis, TMB 35.67 mut/Mb (Pembrolizumab) - Angiosarcoma, TMB 16.1 mut/Mb (Pembrolizumab); - Undifferentiated pleomorphic sarcoma, MSI, TMB 18.8 mut/Mb (Pembrolizumab); - Cutaneous angiosarcoma, PALB2 pathogenic germline variant (Olaparib); - Chondrosarcoma IDH1 R132L (Ivosidenib)NoTranscriptomic biomarkersMG+MD (59)29 biomarkersCD8+ T cell number; PDL1 expression level; SLFN11 expression level; SMARCB1 expression; CD8+ T cell numberNoDiagnostic biomarkersMG+MD (59)9 biomarkersNAB2-STAT6; MXI1-NUTM1; EWSR1-NR4A3; EWSR1-FLI1; EWSR1-CREB3L1; NAB2-STAT6----*RNA analysis failed for 2 patients. Therefore, any expression based analysis was performed on n=20 and n=39 for the MG and MD cohort, respectively. **Tumor mutational burden is considered high for FFPE samples when TMB>8mut/Mb.