Introduction: Prostate cancer is the second-most commonly occurring cancer and the fifth major cause of death among men worldwide. Early diagnosis and treatment planning are very crucial in reducing the mortality rate due to prostate cancer. Gleason grading is the most used prostate cancer prognosis tool by doctors for a long time. It is used to determine the aggressiveness of the cancer for planning treatment options. The process requires very trained pathologists to look at multiple biopsy samples under the microscope and assign a grade to the cancer based on its severity. Methods: In this work, we are adding Gleason grading capabilities to prostate-specific membrane antigen positron emission tomography/ computed tomography (PSMA PET-CT) scans for tumor habitats and classify them as aggressive or indolent type. Tagging habitats with Gleason grade to categorize them as aggressive or indolent type helps in biopsy planning to extract the right tissue samples and tagging helps to target aggressive tumors during radiation therapy. We have developed a machine learning-based model to automatically classify tumor habitat regions of interest from PSMA PET and CT imaging data into Gleason grade groups of indolent and aggressive. Results: The 68Ga-PSMA PET-CT scans are very effective in detecting the presence of different habitats within the tumor with distinct volumes, each with a specific combination of flow, cell density, necrosis, and edema. Habitat distribution through tumor heterogeneity analysis in patients with prostate cancers can be enabled to discriminate between cancers that progress quickly and those that are more indolent. Conclusion: We have developed an AI model to classify habitat tumors present in the gross tumor volume into indolent and aggressive types based on the ground truth generated using Gleason grade groups on pathology samples by Healthcare Global Cancer Hospital, Bangalore, India. Habitat analysis helps radiotherapists to target active tumor cells within gross tumor volume and helps in selecting the right tissue for performing biopsy. The currently developed model is performing with an overall accuracy of 90% on test data.

We sought to determine whether specific taxa in the communities of the C57BL/6J mouse intestinal microbiome were associated with survival after the LD 50/30 dose of total body irradiation (TBI), and if administration of a second-generation probiotic producing anti-inflammatory Interleukin-22 (IL-22) mitigated Gastrointestinal Syndrome inducing doses of total body irradiation (TBI). Materials/Methods: Female C57BL/6J mice were irradiated to LD 50/30 9.25 Gy TBI, or 19.75 Gy whole abdominal irradiation, and evaluated for primary endpoint of survival and secondary endpoint of expression of inflammatory proteins and bone marrow CFU-GEMMs per 10 4 cells. Daily collected fecal samples were analyzed for 16sRNA associated with 15 major taxa in the intestinal microbiome. Second-generation probiotic Lactobacillus reuteri or Escherichia-coli producing IL-22 (LR-IL-22 or E. coli-IL-22, respectively) was administered to subgroups by gavage at 24 hours after irradiation. The results were compared to subcutaneous administration of IL-22 (n Z 12). Results: Thirty-day TBI survivors of 9.25 Gy had at day 14 a predictive increased relative abundance of Lactobacillus, Roseburia, and Akkermansia, compared to other taxa, as did radiation mitigator treated (G-CSF or JP4-039) mice. Administration of LR-IL-22 at 24 hours after irradiation increased survival (p Z 0.0144), as did E. coli-IL-22. GFP-IL-22 fusion protein producing probiotics showed uptake in intestinal villi at 2 h after gavage and clearance by day 5. At 24 hrs. after 9.25 Gy TBI, mice with 4 antibiotic-cleared intestinal microbiomes (5 weeks administration in drinking water of vancomycin, neomycin trisulfate, metronidazole, and ampicillin) had increased survival when treated with E. coli-IL-22, (p < 0.0001). On day 5 after 9.25 Gy TBI, the intestine and bone marrow were isolated. Luminex assay showed significantly decreased inflammatory proteins in mice gavaged with LR-IL-22, and bone marrow had significantly increased CFU-GEMMs per 10 4 cells compared to 9.25 Gy only (15.1 AE 1.1 and 9.1 AE 1.5, respectively, p Z 0.0351). Whole abdomen irradiation to 19.75 Gy followed by gavage at 24 hrs. of LR-IL-22, or E. coli-IL-22 significantly increased survival (p Z 0.0138, 0.0473). Conclusion: These data indicate that the relative abundance of specific taxa in the intestinal microbiome correlates with survival after total body irradiation. Furthermore, gavage of LR-IL-22 improves survival after GI Syndrome inducing doses of irradiation. Elucidation of the molecular mechanism of interaction of pro-survival microbiome communities with intestinal stem cells and regenerating crypts should identify new targets for intestinal radiation protection and mitigation.

Purpose/Objective(s): Radiotherapy is one of the mainstay treatment modalities for the cervical cancer. In Vitro evidences suggest that radiotherapy (RT) can kill various blood cells including lymphocytes. However, there is no valid evidence from human demonstrated blood cytopenia and no knowledge of individual responses associated with immune system functions. This study aimed to apply the FACS technology to investigate the immune cells subtype distribution and changes after radiotherapy in patients with cervical cancer. Materials/Methods: The human blood samples were obtained in EDTA coated tubes in accordance to ethic committee approved prospective study, where all patients signed the informed written consent. Briefly, the blood was first centrifuged with 1600 x g, 4 C and the buffy coat was stored in 90%FBS+10%DMSO gradually to-80 C. The following fluorochrome-conjugated surface antibodies were stained: CD11b, CD45, CD4, CD8a, CD19, CD56, and CD3. The cells were then fixed and permeated, followed by staining with the intracellular antibody FOXP3 and then detected by FACS machine. The percentage of immune cell subtypes at 3 time points from 6 patients (pre-RT, 2 weeks and 4 weeks) were compared using repeated analysis of variance (ANOVA) in GraphPad Prism (version 8.01). P<0.05 level was considered as statistically significant. Results: The percentage of the CD45 + lymphocytes was significantly decreased after 4 weeks of RT (mean: 85.15 vs. 56.7, P Z 0.048). The percentages of CD45 + CD19 + B cells and a total CD45 + CD3 + T cells were changed numerically with a P-value reaching significance (P Z 0.0537 and 0.0502, respectively). The percentage of CD45 + CD3-CD56 + naturally killer cells (NK), CD11b + myeloid and CD45 + CD3 + CD8 + CD56 + natural killer T cells (NKT,), CD45 + CD3 + CD4 + FOXP3 + Treg, CD8 + Cytotoxic T cell and CD4 + Helper T cells didn't show remarkable change. For individual response, 3 patients (50%) showed increased level in myeloid subtype. 5 patients (83.3%) displayed an increased percentage of lymphocytes. 2 patients (33.3%) showed increased trend of NK cells. In addition, 4 patients (66.66%) was significantly decreased in B cells percentage. All patients displayed the same T cell trend. 2 patients (33.33%) was decreased in cytotoxic T cells after RT. Interestingly, the NKT cells change to zero after RT in all patients. For T helper cells, 1 patient (16.6%) remarkedly increased. 1 patient (16.6%) was increased and others was decreased in Treg cells percentage. Conclusion: Radiation alters the lymphocyte subtypes in cervical cancer patient, with remarkable different individual responses, suggesting the differences in radio sensitivities although small sample size. The interplay between the immune system and radiotherapy immunomodulation through differential lymphocyte killing may serve a promising blood biomarker for treatment responses. Future studies with larger number of patients are needed to confirm these findings.

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