Prediction of clinical outcomes using the pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) system

AbstractBiological and molecular heterogeneity of human diseases especially cancers contributes to variations in treatment response, clinical outcome, and survival. The addition of new disease- and condition-specific biomarkers to existing clinical markers to track cancer heterogeneity provides possibilities for further assisting clinicians in predicting clinical outcomes and making choices of treatment options. Ionization patterns derived from biological specimens can be adapted for use with existing clinical markers for early detection, patient risk stratification, treatment decision making, and monitoring disease progression. In order to demonstrate the application of pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) for human diseases to predict the outcome of diseases, we analyzed the ionized spectral signals generated by instrument ACB2000 (ACBirox universal detector 2000, ACBirox LLC, NJ, USA) from the serum samples of Mantle Cell Lymphoma (MCL) patients. Here, we have used mantle cell lymphoma as a disease model for a conceptual study only and based on the ionization patterns of the analyzed serum samples, we developed a multivariate algorithm comprised of variable selection and reduction steps followed by receiver operating characteristic curve (ROC) analysis to predict the probability of a good or poor clinical outcome as a means of estimating the likely success of a particular treatment option. Our preliminary study performed with small cohort provides a proof of concept demonstrating the ability of this system to predict the clinical outcome for human diseases with high accuracy suggesting the promising application of pyrolysis, gas chromatography, and differential mobility spectrometry (Py-GC-DMS) in the field of medicine

Fibroblast growth factor-2 (FGF2) and syndecan-1 (SDC1) are potential biomarkers for putative circulating CD15+/CD30+ cells in poor outcome Hodgkin lymphoma patients.

BACKGROUND: High risk, unfavorable classical Hodgkin lymphoma (cHL) includes those patients with primary refractory or early relapse, and progressive disease. To improve the availability of biomarkers for this group of patients, we investigated both tumor biopsies and peripheral blood leukocytes (PBL) of untreated (chemo-naïve, CN) Nodular Sclerosis Classic Hodgkin Lymphoma (NS-cHL) patients for consistent biomarkers that can predict the outcome prior to frontline treatment. METHODS AND MATERIALS: Bioinformatics data mining was used to generate 151 candidate biomarkers, which were screened against a library of 10 HL cell lines. Expression of FGF2 and SDC1 by CD30+ cells from HL patient samples representing good and poor outcomes were analyzed by qRT-PCR, immunohistochemical (IHC), and immunofluorescence analyses. RESULTS: To identify predictive HL-specific biomarkers, potential marker genes selected using bioinformatics approaches were screened against HL cell lines and HL patient samples. Fibroblast Growth Factor-2 (FGF2) and Syndecan-1 (SDC1) were overexpressed in all HL cell lines, and the overexpression was HL-specific when compared to 116 non-Hodgkin lymphoma tissues. In the analysis of stratified NS-cHL patient samples, expression of FGF2 and SDC1 were 245 fold and 91 fold higher, respectively, in the poor outcome (PO) group than in the good outcome (GO) group. The PO group exhibited higher expression of the HL marker CD30, the macrophage marker CD68, and metastatic markers TGFβ1 and MMP9 compared to the GO group. This expression signature was confirmed by qualitative immunohistochemical and immunofluorescent data. A Kaplan-Meier analysis indicated that samples in which the CD30+ cells carried an FGF2+/SDC1+ immunophenotype showed shortened survival. Analysis of chemo-naive HL blood samples suggested that in the PO group a subset of CD30+ HL cells had entered the circulation. These cells significantly overexpressed FGF2 and SDC1 compared to the GO group. The PO group showed significant down-regulation of markers for monocytes, T-cells, and B-cells. These expression signatures were eliminated in heavily pretreated patients. CONCLUSION: The results suggest that small subsets of circulating CD30+/CD15+ cells expressing FGF2 and SDC1 represent biomarkers that identify NS-cHL patients who will experience a poor outcome (primary refractory and early relapsing)

LUMINOS-102: Lerapolturev with and without α-PD- 1 in unresectable α-PD- 1 refractory melanoma

Lerapolturev (lera, formerly PVSRIPO) is a novel poliovirus based intratumoral immunotherapy that infects both cancer cells and antigen-presenting cells (APCs) via CD155, the poliovirus receptor. Lera has direct anticancer effects while also generating type I/III interferon-dominated inflammation and anti-tumor T-cell priming and activation via infection of local APCs. LUMINOS-102 (NCT04577807) is a multi-center, open-label, two-arm randomized Phase 2 study investigating the efficacy and safety of lera ± α-PD- 1 in patients with unresectable melanoma who failed prior α-PD- 1 therapy. Cross-over to the α-PD- 1 arm is permitted after progression, PR for ≥6 mo or 6 mo on treatment with SD. The maximum initial lera dose was 6x108 TCID50 /visit every 3 or 4 weeks (Q3/4 W). As of March 2022, the maximum lera dose was increased to 1.6 x 109 TCID50/visit, every week (QW) for 7 weeks (induction), followed by Q3/4 W dosing (maintenance). As of 20-Jun- 2022, 21 participants (10 male, 11 female, median 64 yrs) received lera (n = 14 at initial dose, Q3/4 W; n = 4 at increased dose, Q3/4 W; n = 3 at increased dose, QW) ± αPD-1. Five patients are currently on treatment. With the initial regimen, no objective responses and a CBR of 7% were observed. However, with the higher dose regimen, 1 complete response and a CBR of 71% (5/7) has been observed. Two of 4 participants with stable disease have evidence of response (1 with resolution of uninjected lung metastasis, 1 with decreased PET signal in injected and uninjected lesions receiving combination therapy). The only treatment related AE in \u3e1 pt was fatigue (19%, all grade 1 or 2). No dose-limiting toxicities or treatment-related SAEs were reported. Multiplex-IF analysis of on-treatment tumor biopsies will be presented. Lera ± αPD-1 is well tolerated, with early signs of efficacy at the higher dose level. Enrollment and randomization are ongoing

Kallikrein family proteases KLK6 and KLK7 are potential early detection and diagnostic biomarkers for serous and papillary serous ovarian cancer subtypes.

BACKGROUND: Early detection of ovarian cancer remains a challenge due to widespread metastases and a lack of biomarkers for early-stage disease. This study was conducted to identify relevant biomarkers for both laparoscopic and serum diagnostics in ovarian cancer. METHODS: Bioinformatics analysis and expression screening in ovarian cancer cell lines were employed. Selected biomarkers were further validated in bio-specimens of diverse cancer types and ovarian cancer subtypes. For non-invasive detection, biomarker proteins were evaluated in serum samples from ovarian cancer patients. RESULTS: Two kallikrein (KLK) serine protease family members (KLK6 and KLK7) were found to be significantly overexpressed relative to normal controls in most of the ovarian cancer cell lines examined. Overexpression of KLK6 and KLK7 mRNA was specific to ovarian cancer, in particular to serous and papillary serous subtypes. In situ hybridization and histopathology further confirmed significantly elevated levels of KLK6 and KLK7 mRNA and proteins in tissue epithelium and a lack of expression in neighboring stroma. Lastly, KLK6 and KLK7 protein levels were significantly elevated in serum samples from serous and papillary serous subtypes in the early stages of ovarian cancer, and therefore could potentially decrease the high false negative rates found in the same patients with the common ovarian cancer biomarkers human epididymis protein 4 (HE4) and cancer antigen 125 (CA-125). CONCLUSION: KLK6 and KLK7 mRNA and protein overexpression is directly associated with early-stage ovarian tumors and can be measured in patient tissue and serum samples. Assays based on KLK6 and KLK7 expression may provide specific and sensitive information for early detection of ovarian cancer

Protein Calorie Malnutrition, Nutritional Intervention and Personalized Cancer Care

Cancer patients often experience weight loss caused by protein calorie malnutrition (PCM) during the course of the disease or treatment. PCM is expressed as severe if the patient has two or more of the following characteristics: obvious significant muscle wasting, loss of subcutaneous fat; nutritional intake of \u3c50% of recommended intake for 2 weeks or more; bedridden or otherwise significantly reduced functional capacity; weight loss of \u3e2% in 1 week, 5% in 1 month, or 7.5% in 3 months. Cancer anorexiacachexia syndrome (CACS) is a multifactorial condition of advanced PCM associated with underlying illness (in this case cancer) and is characterized by loss of muscle with or without loss of fat mass. Cachexia is defined as weight loss of more than 5% of body weight in 12 months or less in the presence of chronic disease. Hence with a chronic illness on board even a small amount of weight loss can open the door to cachexia. These nutritional challenges can lead to severe morbidity and mortality in cancer patients. In the clinic, the application of personalized medicine and the ability to withstand the toxic effects of anti-cancer therapies can be optimized when the patient is in nutritional homeostasis and is free of anorexia and cachexia. Routine assessment of nutritional status and appropriate intervention are essential components of the effort to alleviate effects of malnutrition on quality of life and survival of patients

Safety and Efficacy of Donor T Cells Engineered with Herpes Simplex Virus Thymidine-Kinase Suicide Gene (TK Cells) Given after T-Cell Depleted (TCD) Haploidentical Hematopoietic Transplantation (Haplo-HSCT): Results of a 14-Year Follow-Up in 45 Patients

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The use of transcriptomic data in developing biomarkers in breast cancer

Abstract HER2 and hormone receptors are biomarkers for selecting breast cancer therapy and predicting outcomes. In the era of antibody‐drug conjugates (ADC), a relatively low HER2 expression level is adequate for targeting tumor cells. We explored the potential of RNA profiling, determined by next generation sequencing (NGS), to provide more flexible clinical biomarkers as compared with immunohistochemistry (IHC) or fluorescent in situ hybridization (FISH). Data from 57 breast cancers was used to study biomarker levels as detected by routine clinical transcriptomic tests. HER2 (ERBB2), estrogen receptor alpha (ESR1), and androgen receptor (AR) mRNA levels were compared with IHC and FISH results. There was a significant overlap in the levels of ERBB2 mRNA between cases scored by IHC as zero, 1+, and 2+. This variation correlated with progression‐free survival (PFS). Similarly, the ESR1 RNA accurately reflected estrogen receptor (ER) status. Patients with high AR mRNA had better PFS (p = 0.05). Patients expressing high ER and AR levels had better PFS than those expressing low ESR1 and AR (p = 0.03). These findings suggest that RNA analysis can be an alternative to IHC and FISH and provides continuous data that can better determine cut‐off points for predicting response to ADC

Combining cell-free RNA with cell-free DNA in liquid biopsy for hematologic and solid tumors

Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P 0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response