Murine allogeneic CAR T cells integrated before or early after posttransplant cyclophosphamide exert antitumor effects.

Relapse limits the therapeutic efficacy both of chimeric antigen receptor (CAR) T cells and allogeneic hematopoietic cell transplantation (allo-HCT). Patients may undergo these therapies sequentially to prevent or treat relapsed malignancy. However, direct integration of the 2 therapies has been avoided over concerns for potential induction of graft-versus-host disease (GVHD) by allogeneic CAR T cells. We have shown in murine T-cell-replete MHC-haploidentical allo-HCT that suppressive mechanisms induced immediately after posttransplant cyclophosphamide (PTCy), given on days +3/+4, prevent GVHD induction by alloreactive T cells infused as early as day +5. Therefore, we hypothesized that allogeneic CAR T cells given in a similarly integrated manner in our murine MHC-haploidentical allo-HCT model may safely exert antitumor effects. Indeed, allogeneic anti-CD19 CAR T cells given early after (day +5) PTCy or even prior to (day 0) PTCy cleared leukemia without exacerbating the cytokine release syndrome occurring from the MHC-haploidentical allo-HCT or interfering with PTCy-mediated GVHD prevention. Meanwhile, CAR T-cell treatment on day +9 or day +14 was safe but less effective, suggesting a limited therapeutic window. CAR T cells infused before PTCy were not eliminated, but surviving CAR T cells continued to proliferate highly and expand despite PTCy. In comparison with infusion on day +5, CAR T-cell infusion on day 0 demonstrated superior clinical efficacy associated with earlier CAR T-cell expansion, higher phenotypic CAR T-cell activation, less CD4+CD25+Foxp3+ CAR T-cell recovery, and transcriptional changes suggesting increased activation of CD4+ CAR T cells and more cytotoxic CD8+ CAR T cells. This study provides mechanistic insight into PTCy's impact on graft-versus-tumor immunity and describes novel approaches to integrate CAR T cells and allo-HCT that may compensate for deficiencies of each individual approach.

Comparison of Large Language Models in Answering Immuno-Oncology Questions: A Cross-Sectional Study.

BACKGROUND: The capability of large language models (LLMs) to understand and generate human-readable text has prompted the investigation of their potential as educational and management tools for patients with cancer and healthcare providers. MATERIALS AND METHODS: We conducted a cross-sectional study aimed at evaluating the ability of ChatGPT-4, ChatGPT-3.5, and Google Bard to answer questions related to 4 domains of immuno-oncology (Mechanisms, Indications, Toxicities, and Prognosis). We generated 60 open-ended questions (15 for each section). Questions were manually submitted to LLMs, and responses were collected on June 30, 2023. Two reviewers evaluated the answers independently. RESULTS: ChatGPT-4 and ChatGPT-3.5 answered all questions, whereas Google Bard answered only 53.3% (P < .0001). The number of questions with reproducible answers was higher for ChatGPT-4 (95%) and ChatGPT3.5 (88.3%) than for Google Bard (50%) (P < .0001). In terms of accuracy, the number of answers deemed fully correct were 75.4%, 58.5%, and 43.8% for ChatGPT-4, ChatGPT-3.5, and Google Bard, respectively (P = .03). Furthermore, the number of responses deemed highly relevant was 71.9%, 77.4%, and 43.8% for ChatGPT-4, ChatGPT-3.5, and Google Bard, respectively (P = .04). Regarding readability, the number of highly readable was higher for ChatGPT-4 and ChatGPT-3.5 (98.1%) and (100%) compared to Google Bard (87.5%) (P = .02). CONCLUSION: ChatGPT-4 and ChatGPT-3.5 are potentially powerful tools in immuno-oncology, whereas Google Bard demonstrated relatively poorer performance. However, the risk of inaccuracy or incompleteness in the responses was evident in all 3 LLMs, highlighting the importance of expert-driven verification of the outputs returned by these technologies.

Utility of Large Language Models for Health Care Professionals and Patients in Navigating Hematopoietic Stem Cell Transplantation: Comparison of the Performance of ChatGPT-3.5, ChatGPT-4, and Bard.

BACKGROUND: Artificial intelligence is increasingly being applied to many workflows. Large language models (LLMs) are publicly accessible platforms trained to understand, interact with, and produce human-readable text; their ability to deliver relevant and reliable information is also of particular interest for the health care providers and the patients. Hematopoietic stem cell transplantation (HSCT) is a complex medical field requiring extensive knowledge, background, and training to practice successfully and can be challenging for the nonspecialist audience to comprehend. OBJECTIVE: We aimed to test the applicability of 3 prominent LLMs, namely ChatGPT-3.5 (OpenAI), ChatGPT-4 (OpenAI), and Bard (Google AI), in guiding nonspecialist health care professionals and advising patients seeking information regarding HSCT. METHODS: We submitted 72 open-ended HSCT-related questions of variable difficulty to the LLMs and rated their responses based on consistency-defined as replicability of the response-response veracity, language comprehensibility, specificity to the topic, and the presence of hallucinations. We then rechallenged the 2 best performing chatbots by resubmitting the most difficult questions and prompting to respond as if communicating with either a health care professional or a patient and to provide verifiable sources of information. Responses were then rerated with the additional criterion of language appropriateness, defined as language adaptation for the intended audience. RESULTS: ChatGPT-4 outperformed both ChatGPT-3.5 and Bard in terms of response consistency (66/72, 92%; 54/72, 75%; and 63/69, 91%, respectively; P=.007), response veracity (58/66, 88%; 40/54, 74%; and 16/63, 25%, respectively; P<.001), and specificity to the topic (60/66, 91%; 43/54, 80%; and 27/63, 43%, respectively; P<.001). Both ChatGPT-4 and ChatGPT-3.5 outperformed Bard in terms of language comprehensibility (64/66, 97%; 53/54, 98%; and 52/63, 83%, respectively; P=.002). All displayed episodes of hallucinations. ChatGPT-3.5 and ChatGPT-4 were then rechallenged with a prompt to adapt their language to the audience and to provide source of information, and responses were rated. ChatGPT-3.5 showed better ability to adapt its language to nonmedical audience than ChatGPT-4 (17/21, 81% and 10/22, 46%, respectively; P=.03); however, both failed to consistently provide correct and up-to-date information resources, reporting either out-of-date materials, incorrect URLs, or unfocused references, making their output not verifiable by the reader. CONCLUSIONS: In conclusion, despite LLMs' potential capability in confronting challenging medical topics such as HSCT, the presence of mistakes and lack of clear references make them not yet appropriate for routine, unsupervised clinical use, or patient counseling. Implementation of LLMs' ability to access and to reference current and updated websites and research papers, as well as development of LLMs trained in specialized domain knowledge data sets, may offer potential solutions for their future clinical application.

A hidden Markov modeling approach for identifying tumor subclones in next-generation sequencing studies.

Allele-specific copy number alteration (ASCNA) analysis is for identifying copy number abnormalities in tumor cells. Unlike normal cells, tumor cells are heterogeneous as a combination of dominant and minor subclones with distinct copy number profiles. Estimating the clonal proportion and identifying mainclone and subclone genotypes across the genome are important for understanding tumor progression. Several ASCNA tools have recently been developed, but they have been limited to the identification of subclone regions, and not the genotype of subclones. In this article, we propose subHMM, a hidden Markov model-based approach that estimates both subclone region and region-specific subclone genotype and clonal proportion. We specify a hidden state variable representing the conglomeration of clonal genotype and subclone status. We propose a two-step algorithm for parameter estimation, where in the first step, a standard hidden Markov model with this conglomerated state variable is fit. Then, in the second step, region-specific estimates of the clonal proportions are obtained by maximizing region-specific pseudo-likelihoods. We apply subHMM to study renal cell carcinoma datasets in The Cancer Genome Atlas. In addition, we conduct simulation studies that show the good performance of the proposed approach. The R source code is available online at https://dceg.cancer.gov/tools/analysis/subhmm. Expectation-Maximization algorithm; Forward-backward algorithm; Somatic copy number alteration; Tumor subclones.

Integrative molecular characterisation of gallbladder cancer reveals micro-environment-associated subtypes.

BACKGROUND & AIMS: Gallbladder cancer (GBC) is the most common type of biliary tract cancer, but the molecular mechanisms involved in gallbladder carcinogenesis remain poorly understood. In this study, we applied integrative genomics approaches to characterise GBC and explore molecular subtypes associated with patient survival. METHODS: We profiled the mutational landscape of GBC tumours (whole-exome sequencing on 92, targeted sequencing on 98, in total 190 patients). In a subset (n = 45), we interrogated the matched transcriptomes, DNA methylomes, and somatic copy number alterations. We explored molecular subtypes identified through clustering tumours by genes whose expression was associated with survival in 47 tumours and validated subtypes on 34 publicly available GBC cases. RESULTS: Exome analysis revealed TP53 was the most mutated gene. The overall mutation rate was low (median 0.82 Mut/Mb). APOBEC-mediated mutational signatures were more common in tumours with higher mutational burden. Aflatoxin-related signatures tended to be highly clonal (present in ≥50% of cancer cells). Transcriptome-wide survival association analysis revealed a 95-gene signature that stratified all GBC patients into 3 subtypes that suggested an association with overall survival post-resection. The 2 poor-survival subtypes were associated with adverse clinicopathologic features (advanced stage, pN1, pM1), immunosuppressive micro-environments (myeloid-derived suppressor cell accumulation, extensive desmoplasia, hypoxia) and T cell dysfunction, whereas the good-survival subtype showed the opposite features. CONCLUSION: These data suggest that the tumour micro-environment and immune profiles could play an important role in gallbladder carcinogenesis and should be evaluated in future clinical studies, along with mutational profiles. LAY SUMMARY: Gallbladder cancer is highly fatal, and its causes are poorly understood. We evaluated gallbladder tumours to see if there were differences between tumours in genetic information such as DNA and RNA. We found evidence of aflatoxin exposure in these tumours, and immune cells surrounding the tumours were associated with survival.

Modeling repeated labor curves in consecutive pregnancies: Individualized prediction of labor progression from previous pregnancy data.

The measurement of cervical dilation of a pregnant woman is used to monitor the progression of labor until 10 cm when pushing begins. There is anecdotal evidence that labor tracks across repeated pregnancies; moreover, no statistical methodology has been developed to address this important issue, which can help obstetricians make more informed clinical decisions about an individual woman's progression. Motivated by the NICHD Consecutive Pregnancies Study (CPS), we propose new methodology for analyzing labor curves across consecutive pregnancies. Our focus is both on studying the correlation between repeated labor curves on the same woman and on using the cervical dilation data from prior pregnancies to predict subsequent labor curves. We propose a hierarchical random effects model with a random change point that characterizes repeated labor curves within and between women to address these issues. We employ Bayesian methodology for parameter estimation and prediction. Model diagnostics to examine the appropriateness of the hierarchical random effects structure for characterizing the dependence structure across consecutive pregnancies are also proposed. The methodology was used in analyzing the CPS data and in developing a predictor for labor progression that can be used in clinical practice.

hsegHMM: hidden Markov model-based allele-specific copy number alteration analysis accounting for hypersegmentation.

BACKGROUND: Somatic copy number alternation (SCNA) is a common feature of the cancer genome and is associated with cancer etiology and prognosis. The allele-specific SCNA analysis of a tumor sample aims to identify the allele-specific copy numbers of both alleles, adjusting for the ploidy and the tumor purity. Next generation sequencing platforms produce abundant read counts at the base-pair resolution across the exome or whole genome which is susceptible to hypersegmentation, a phenomenon where numerous regions with very short length are falsely identified as SCNA. RESULTS: We propose hsegHMM, a hidden Markov model approach that accounts for hypersegmentation for allele-specific SCNA analysis. hsegHMM provides statistical inference of copy number profiles by using an efficient E-M algorithm procedure. Through simulation and application studies, we found that hsegHMM handles hypersegmentation effectively with a t-distribution as a part of the emission probability distribution structure and a carefully defined state space. We also compared hsegHMM with FACETS which is a current method for allele-specific SCNA analysis. For the application, we use a renal cell carcinoma sample from The Cancer Genome Atlas (TCGA) study. CONCLUSIONS: We demonstrate the robustness of hsegHMM to hypersegmentation. Furthermore, hsegHMM provides the quantification of uncertainty in identifying allele-specific SCNAs over the entire chromosomes. hsegHMM performs better than FACETS when read depth (coverage) is uneven across the genome.

A Bayesian approach for analyzing zero-inflated clustered count data with dispersion.

In practice, count data may exhibit varying dispersion patterns and excessive zero values; additionally, they may appear in groups or clusters sharing a common source of variation. We present a novel Bayesian approach for analyzing such data. To model these features, we combine the Conway-Maxwell-Poisson distribution, which allows both overdispersion and underdispersion, with a hurdle component for the zeros and random effects for clustering. We propose an efficient Markov chain Monte Carlo sampling scheme to obtain posterior inference from our model. Through simulation studies, we compare our hurdle Conway-Maxwell-Poisson model with a hurdle Poisson model to demonstrate the effectiveness of our Conway-Maxwell-Poisson approach. Furthermore, we apply our model to analyze an illustrative dataset containing information on the number and types of carious lesions on each tooth in a population of 9-year-olds from the Iowa Fluoride Study, which is an ongoing longitudinal study on a cohort of Iowa children that began in 1991.

A nested case-control study of polychlorinated biphenyls, organochlorine pesticides, and thyroid cancer in the Janus Serum Bank cohort.

BACKGROUND: Polychlorinated biphenyls (PCBs) and organochlorine pesticides have been associated with altered thyroid hormone levels in humans, but their relationship with thyroid cancer is unknown. METHODS: We conducted a nested case-control study of thyroid cancer in the Norwegian Janus Serum Bank cohort using pre-diagnostic blood samples from 1972 to 1985. Incident thyroid cancer (n = 108) was ascertained through 2008. Controls were matched 2:1 by age, date of blood draw, gender, and county. We used gas chromatography/mass spectrometry to quantify 36 PCB congeners and metabolites of pesticides DDT, chlordane, hexachlorocyclohexane, and hexachlorobenzene. PCBs and pesticide metabolites were evaluated individually and summed by degree of chlorination and parent compound, respectively. Odds ratios (OR) and 95% confidence intervals (CI) were computed using conditional logistic regression per specified increase in lipid-adjusted concentration. We additionally stratified analyses by birth cohort (1923-1932, 1933-1942, 1943-1957). RESULTS: Increasing concentration of DDT metabolites (ORper 1000 ng/g = 0.80, 95%CI = 0.66-0.98) was inversely associated with thyroid cancer. Associations for PCBs were null or in inverse direction. We observed interactions for total PCBs, moderately-chlorinated PCBs, and chlordane metabolites with birth cohort (p ≤ 0.04). Among participants born 1943-1957, total PCBs (ORper 100 ng/g = 1.25, 95%CI = 1.00-1.56), moderately-chlorinated PCBs (ORper 100 ng/g = 1.31, 95%CI = 1.01-1.70), and chlordane metabolites (ORper 10 ng/g = 1.78, 95%CI = 1.09-2.93) were positively associated with thyroid cancer. For individuals born before 1943, associations were generally null or in the inverse direction. CONCLUSIONS: Emissions of PCBs and OC pesticides varied over time. Different risk patterns by birth cohort suggest the potential importance of timing of exposure in thyroid cancer risk. Further evaluation of these associations is warranted.

Marginal regression models for clustered count data based on zero-inflated Conway-Maxwell-Poisson distribution with applications.

Community water fluoridation is an important public health measure to prevent dental caries, but it continues to be somewhat controversial. The Iowa Fluoride Study (IFS) is a longitudinal study on a cohort of Iowa children that began in 1991. The main purposes of this study (http://www.dentistry.uiowa.edu/preventive-fluoride-study) were to quantify fluoride exposures from both dietary and nondietary sources and to associate longitudinal fluoride exposures with dental fluorosis (spots on teeth) and dental caries (cavities). We analyze a subset of the IFS data by a marginal regression model with a zero-inflated version of the Conway-Maxwell-Poisson distribution for count data exhibiting excessive zeros and a wide range of dispersion patterns. In general, we introduce two estimation methods for fitting a ZICMP marginal regression model. Finite sample behaviors of the estimators and the resulting confidence intervals are studied using extensive simulation studies. We apply our methodologies to the dental caries data. Our novel modeling incorporating zero inflation, clustering, and overdispersion sheds some new light on the effect of community water fluoridation and other factors. We also include a second application of our methodology to a genomic (next-generation sequencing) dataset that exhibits underdispersion.

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity.

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation non-uniformly to secure against the possibility that favorable growth conditions, which puts sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early utilize a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay non-sporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

Preclinical Evaluation of a Novel Series of Polyfluorinated Thalidomide Analogs in Drug-Resistant Multiple Myeloma.

Immunomodulatory imide drugs (IMiDs) play a crucial role in the treatment landscape across various stages of multiple myeloma. Despite their evident efficacy, some patients may exhibit primary resistance to IMiD therapy, and acquired resistance commonly arises over time leading to inevitable relapse. It is critical to develop novel therapeutic options to add to the treatment arsenal to overcome IMiD resistance. We designed, synthesized, and screened a new class of polyfluorinated thalidomide analogs and investigated their anti-cancer, anti-angiogenic, and anti-inflammatory activity using in vitro and ex vivo biological assays. We identified four lead compounds that exhibit potent anti-myeloma, anti-angiogenic, anti-inflammatory properties using three-dimensional tumor spheroid models, in vitro tube formation, and ex vivo human saphenous vein angiogenesis assays, as well as the THP-1 inflammatory assay. Western blot analyses investigating the expression of proteins downstream of cereblon (CRBN) reveal that Gu1215, our primary lead candidate, exerts its activity through a CRBN-independent mechanism. Our findings demonstrate that the lead compound Gu1215 is a promising candidate for further preclinical development to overcome intrinsic and acquired IMiD resistance in multiple myeloma.

Pulmonary Metastasectomy for Adrenocortical Carcinoma-Not If, but When.

BACKGROUND: Adrenocortical carcinoma (ACC) commonly metastasizes to the lungs, and pulmonary metastasectomy (PM) is utilized due to limited systemic options. METHODS: All ACC patients with initially only lung metastases (LM) from a single institution constituted this observational case series. Kaplan-Meier and Cox proportional hazard analyses evaluated the association with potential prognostic factors and outcomes. Overall survival (OS) was calculated from the date of the PM or, in those patients who did not undergo surgery, from the development of LM. RESULTS: A total of 75 ACC patients over a 45-year period met the criteria; 52 underwent PM, and 23 did not. The patients undergoing PM had a median OS of 3.1 years (95% CI: 2.4, 4.7 years) with the 5- and 10-year OS being 35.5% and 32.8%, respectively. The total resected LM did not impact the OS nor the DFS. The patients who developed LM after 11 months from the initial ACC resection had an improved OS (4.2 years; 95% CI: 3.2, NR; p = 0.0096) compared to those developing metastases earlier (2.4 years; 95% CI: 1.6, 2.8). Patients who underwent PM within 11 months of adrenalectomy demonstrated a reduced OS (2.2 years; 95% CI: 1.0, 2.7) compared to those after 11 months (3.6 years, 95% CI: 2.6, NR; p = 0.0045). PM may provide benefit to those patients with LM at presentation (HR: 0.5; p = 0.2827), with the time to first PM as a time-varying covariate. CONCLUSIONS: PM appears to have a role in ACC patients. The number of nodules should not be an exclusion factor. Patients developing LM within a year of primary tumor resection may benefit from waiting before further surgeries, which may provide additional insight into who may benefit from PM.

Current status of National Institutes of Health funding for thoracic surgeons in the United States: Beacon of hope or candle in the wind?

OBJECTIVE: Increasing forces threaten the viability of thoracic surgeon-initiated research, a core component of our academic mission. National Institutes of Health funding is a benchmark of research productivity and innovation. This study examined the current status of National Institutes of Health funding for thoracic surgeons. METHODS: Thoracic surgeon principal investigators on National Institutes of Health-funded grants during June 2010, June 2015, and June 2020 were identified using National Institutes of Health iSearchGrants (version 2.4). American Association of Medical Colleges data were used to identify all surgeons in the United States. Types and total costs of National Institutes of Health-funded grants were compared relative to other surgical specialties. RESULTS: A total of 61 of 4681 (1.3%), 63 of 4484 (1.4%), and 60 of 4497 (1.3%) thoracic surgeons were principal investigators on 79, 76, and 87 National Institutes of Health-funded grants in 2010, 2015, and 2020, respectively; these rates were higher than those for most other surgical specialties (P ≤ .0001). Total National Institutes of Health costs for Thoracic Surgeon-initiated grants increased 57% from 2010 to 2020, outpacing the 33% increase in total National Institutes of Health budget. Numbers and types of grants varied among cardiovascular, transplant, and oncology subgroups. Although the majority of grants and costs were cardiovascular related, increased National Institutes of Health expenditures primarily were due to funding for transplant and oncology grants. Per-capita costs were highest for transplant-related grants during both years. Percentages of R01-to-total costs were constant at 55%. Rates and levels of funding for female versus male thoracic surgeons were comparable. Awards to 5 surgeons accounted for 33% of National Institutes of Health costs for thoracic surgeon principal investigators in 2020; a similar phenomenon was observed for 2010 and 2015. CONCLUSIONS: Long-term structural changes must be implemented to more effectively nurture the next generation of thoracic surgeon scientists.

Tofacitinib to prevent anti-drug antibody formation against LMB-100 immunotoxin in patients with advanced mesothelin-expressing cancers.

Background: LMB-100 is a mesothelin (MSLN)-targeting recombinant immunotoxin (iTox) carrying a Pseudomonas exotoxin A payload that has shown promise against solid tumors, however, efficacy is limited by the development of neutralizing anti-drug antibodies (ADAs). Tofacitinib is an oral Janus Kinase (JAK) inhibitor that prevented ADA formation against iTox in preclinical studies. Methods: A phase 1 trial testing LMB-100 and tofacitinib in patients with MSLN-expressing cancers (pancreatic adenocarcinoma, n=13; cholangiocarcinoma, n=1; appendiceal carcinoma, n=1; cystadenocarcinoma, n=1) was performed to assess safety and to determine if tofacitinib impacted ADA formation. Participants were treated for up to 3 cycles with LMB-100 as a 30-minute infusion on days 4, 6, and 8 at two dose levels (100 and 140 µg/kg) while oral tofacitinib was administered for the first 10 days of the cycle (10 mg BID). Peripheral blood was collected for analysis of ADA levels, serum cytokines and circulating immune subsets. Results: The study was closed early due to occurrence of drug-induced pericarditis in 2 patients. Pericarditis with the combination was not reproducible in a transgenic murine model containing human MSLN. Two of 4 patients receiving all 3 cycles of treatment maintained effective LMB-100 levels, an unusual occurrence. Sustained increases in systemic IL-10 and TNF-α were seen, a phenomenon not observed in prior LMB-100 studies. A decrease in activated T cell subsets and an increase in circulating immunosuppressive myeloid populations occurred. No radiologic decreases in tumor volume were observed. Discussion: Further testing of tofacitinib to prevent ADA formation is recommended in applicable non-malignant disease settings. Clinical trial registration: https://www.clinicaltrials.gov/study/NCT04034238.

Comparison of Large Language Models in Answering Immuno-Oncology Questions: A Cross-Sectional Study.

Background: The capability of large language models (LLMs) to understand and generate human-readable text has prompted the investigation of their potential as educational and management tools for cancer patients and healthcare providers. Materials and Methods: We conducted a cross-sectional study aimed at evaluating the ability of ChatGPT-4, ChatGPT-3.5, and Google Bard to answer questions related to four domains of immuno-oncology (Mechanisms, Indications, Toxicities, and Prognosis). We generated 60 open-ended questions (15 for each section). Questions were manually submitted to LLMs, and responses were collected on June 30th, 2023. Two reviewers evaluated the answers independently. Results: ChatGPT-4 and ChatGPT-3.5 answered all questions, whereas Google Bard answered only 53.3% (p <0.0001). The number of questions with reproducible answers was higher for ChatGPT-4 (95%) and ChatGPT3.5 (88.3%) than for Google Bard (50%) (p <0.0001). In terms of accuracy, the number of answers deemed fully correct were 75.4%, 58.5%, and 43.8% for ChatGPT-4, ChatGPT-3.5, and Google Bard, respectively (p = 0.03). Furthermore, the number of responses deemed highly relevant was 71.9%, 77.4%, and 43.8% for ChatGPT-4, ChatGPT-3.5, and Google Bard, respectively (p = 0.04). Regarding readability, the number of highly readable was higher for ChatGPT-4 and ChatGPT-3.5 (98.1%) and (100%) compared to Google Bard (87.5%) (p = 0.02). Conclusion: ChatGPT-4 and ChatGPT-3.5 are potentially powerful tools in immuno-oncology, whereas Google Bard demonstrated relatively poorer performance. However, the risk of inaccuracy or incompleteness in the responses was evident in all three LLMs, highlighting the importance of expert-driven verification of the outputs returned by these technologies.

Efficacy and safety of PARP inhibitors in metastatic castration-resistant prostate cancer: A systematic review and meta-analysis of clinical trials.

INTRODUCTION: PARP inhibitors (PARPi) are a standard-of-care (SoC) treatment option for patients with metastatic castration-resistant prostate cancer (mCRPC). Several clinical trials have shown the potential of combining PARPi with other anticancer agents. Therefore, we conducted a systematic review and meta-analysis to comprehensively evaluate the efficacy and safety of PARPi in patients with metastatic prostate cancer. METHODS: MEDLINE, Cochrane CENTRAL, EMBASE, CINAHL, and Web of Science were searched on March 22nd, 2023, for phase 2 or 3 clinical trials. Efficacy (progression-free survival [PFS], overall survival [OS], PSA decline >50% [PSA50], and objective response rate [ORR]) and safety outcomes were assessed in the included studies. RESULTS: Seventeen clinical trials (PARPi monotherapy [n = 7], PARPi + androgen-receptor signaling inhibitors [ARSI] [n = 6], and PARPi + immune checkpoint inhibitors [ICI] [n = 4]) were included in the quantitative analyses. PARPi monotherapy improved radiographic PFS and OS over SoC in mCRPC patients with alterations in BRCA1 or BRCA2 genes but not in those with alterations in the ATM gene. Higher rates of PSA50 and ORR were reported in participants treated with PARPi + ARSI than in single-agent PARPi or PARPi + ICI. Although the rate of high-grade adverse events was similar across all groups, treatment discontinuation was higher in patients treated with PARPi-based combinations than PARPi monotherapy. CONCLUSION: The efficacy of PARPi is not uniform across mCRPC patients with alterations in DNA damage repair genes, and optimal patient selection remains a clinical challenge. No unexpected safety signals for this class of agents emerged from this analysis.

GNRH2 Polymorphism in Men With Prostate Cancer Treated With Androgen Deprivation Therapy.

BACKGROUND/AIM: Gonadotropin-releasing hormone 2 (GNRH2) is a poorly-studied peptide hormone that is widely distributed in the central nervous system and expressed in peripheral tissues of mammals. The non-synonymous rs6051545 variant in GNRH2 (A16V) has been linked to higher serum testosterone concentrations. This study investigated whether the A16V variant is associated with altered androgen-deprivation therapy (ADT) progression-free survival (PFS) and overall survival (OS). PATIENTS AND METHODS: We examined the expression of GNRH2 in prostate tissue microarrays comprising normal tissue, prostatic hyperplasia, and prostate cancer using immunofluorescence. We also evaluated the GNRH2 genotype in 131 patients with prostate cancer who received ADT and compared PFS and OS between the variant and wild-type genotypes. RESULTS: GNRH2 was detected in all prostate tissues, although expression did not vary with Gleason grade or disease stage (p=0.71). The GNRH2 A16V genotype was not associated with PFS or OS; however, univariate and multivariate analyses revealed Gleason score and definitive local therapy were each associated with PFS (p≤0.0074), whereas age and Gleason score were associated with OS (p≤0.0046). CONCLUSION: GNRH2 is expressed in normal, hyperplastic, and neoplastic prostate tissues; the A16V variant is not related to treatment outcome or survival.

Posttransplantation cyclophosphamide expands functional myeloid-derived suppressor cells and indirectly influences Tregs.

Posttransplantation cyclophosphamide (PTCy), given on days +3 and +4, reduces graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (HCT), but its immunologic underpinnings are not fully understood. In a T-cell-replete, major histocompatibility complex-haploidentical murine HCT model (B6C3F1→B6D2F1), we previously showed that PTCy rapidly induces suppressive mechanisms sufficient to prevent GVHD induction by non-PTCy-exposed donor splenocytes infused on day +5. Here, in PTCy-treated mice, we found that depleting Foxp3+ regulatory T cells (Tregs) in the initial graft but not the day +5 splenocytes did not worsen GVHD, yet depleting Tregs in both cellular compartments led to fatal GVHD induced by the day +5 splenocytes. Hence, Tregs were necessary to control GVHD induced by new donor cells, but PTCy's impact on Tregs appeared to be indirect. Therefore, we hypothesized that myeloid-derived suppressor cells (MDSCs) play a complementary role. Functionally suppressive granulocytic and monocytic MDSCs were increased in percentages in PTCy-treated mice, and MDSC percentages were increased after administering PTCy to patients undergoing HLA-haploidentical HCT. PTCy increased colony-stimulating factors critical for MDSC development and rapidly promoted the generation of MDSCs from bone marrow precursors. MDSC reduction via anti-Gr1 treatment in murine HCT did not worsen histopathologic GVHD but resulted in decreased Tregs and inferior survival. The clinical implications of these findings, including the potential impact of expanded MDSCs after PTCy on engraftment and cytokine release syndrome, remain to be elucidated. Moreover, the indirect effect that PTCy has on Tregs, which in turn play a necessary role in GVHD prevention by initially transplanted or subsequently infused T cells, requires further investigation.