Sensory deficits are a common manifestation of chemotherapy-induced peripheral neuropathy (CIPN), but validated quantification of symptoms requires cumbersome neurologic testing, which is not routinely performed. We sought to validate a novel, easy to use, quantitative tool for assessing sensory neuropathy in patients undergoing platinum and taxane chemotherapy for the treatment of gynecologic cancer. Patients with gynecologic cancer who were undergoing treatment performed tactile sensory testing using the Bumps device before receiving chemotherapy (baseline), after 2–3 cycles (inter-treatment), after six cycles (completion of treatment), and six months after completing chemotherapy. The Bumps testing device comprises 16 squares, each containing five small circles of different colors. One random circle per square contains a bump of varying height ranging from 14 to 2.5 um arranged in non-sequential decreasing height. Thirty-six patients were enrolled in this study. Two patients withdrew prior to initial testing; of the remaining 34 patients, 28 patients had undergone testing more than once. Compared to baseline testing, 14 of 28 patients (50%) experienced a reduction in tactile sensitivity of at least 1.5 um after two cycles of chemotherapy. Eight patients (28.5%) showed no change in sensitivity thresholds. Of the patients who have completed six cycles of chemotherapy, 9 of 14 patients (64%) had a reduction in tactile sensitivity compared to baseline, and 4 patients (28.5%) showed no change. Compared to baseline testing, 7 of 9 (78%) patients had concordant reductions of tactile sensitivity at both inter-treatment and completion-of-treatment testing times. At Completion-of-treatment testing, these seven patients had a median 5.5 um decrease (4.5 to 12.5) in tactile sensitivity compared to a median 1 um decrease (−0.5 (improvement) to 6.5) in the five patients whose inter-treatment testing showed no change or improvement from baseline testing. The Bumps test allows for a rapid, quantitative measure of neuropathy. While some patients recover sensitivity over time, prolonged deficits are common. Our preliminary data suggest that the early reduction of sensation may predict ongoing and more severe sensory deficits. The ability to predict these changes may compel more expeditious changes to treatment regimens (e.g., dose-reductions, alternative chemotherapies). Early treatment changes could help prevent the length and severity of CIPN symptoms.

Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse effect of platinum and taxane chemotherapy leading to decreased quality of life (QOL) in gynecologic cancer patients. There is currently no validated method to quickly quantify the severity of peripheral neuropathy. We sought to determine whether a novel, easy to use, quantitative tool can assess the extent of CIPN in gynecologic oncology patients. Furthermore, we aimed to compare these results with those of the validated Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity (NTX) questionnaire. We assessed patients with gynecologic cancer undergoing platinum and taxane-based chemotherapy with two different tests: sensory testing using the "Bumps" device and subjective responses from the NTX questionnaire. The data were collected in a prospective fashion. The Bumps test utilizes a device that contains a series of raised bumps at different heights to quantitatively assess the sensory threshold of patients. These tests were given before receiving chemotherapy (baseline), after 2–3 cycles (intertreatment), after 6 cycles (completion of treatment), and 6 months after completing therapy (recovery). A higher score in the NTX questionnaire indicates worsening neuropathy, as does a decreased threshold of sensation in the Bumps test. We then compared the results of the two tests to see if there was a concordant worsening of neuropathy or improvement of neuropathy at each time point. Of the 36 patients enrolled in the study, 27 have completed the intertreatment testing, 14 patients have performed the completion of treatment testing, and 6 patients have completed the recovery testing. Compared to baseline testing, concordant testing between the Bumps and NTX testing was noted for 11 of 27 (41%) patients at intertreatment testing, 10 of 14 (71%) patients at completion of treatment testing, and 3 of 6 (50%) patients at recovery testing. When comparing the completion of treatment testing to intertreatment testing, concordant testing was noted for 5 of 14 (36%) patients. Lastly, in comparing recovery testing to completion of treatment testing, concordant testing was noted for 2 of 6 (33%) patients. Our study allows us to evaluate whether the results of the Bumps test correlate with the already validated NTX test. This would allow for a quantitative measure of neuropathy in addition to the purely subjective measure provided by the NTX test, which would be valuable in predicting QOL changes in patients with CIPN. Preliminary data suggest that a worse/better NTX score does not predict a concordant change in tactile sensitivity evaluated on the Bumps test. Although we may be able to quantify a sensory deficiency, this study highlights that quantifiable deficits may not accurately gauge the effect of CIPN on perceived QOL. We await analysis of the complete dataset but continue to underscore the importance of managing symptoms on patient-reported deficits in order to optimize QOL.

Objectives: Immune cell infiltration is associated with positive ovarian cancer prognosis and is used to predict response to emerging immunotherapies. Multiple methods are used both clinically and in research to quantify immune infiltration, but there is a lack of consensus on the best method. The objective of this study was to compare four methods of measuring immune infiltration: immunohistochemistry for PDL1 (Combined Positive Score - CPS), H&E analysis of immune infiltration (Salgado TIL score), multiparameter immunofluorescence (IHC), and single cell RNA sequencing (scRNAseq). This exploratory work compares these four methods and calculates associations with disease outcomes. Methods: Thirty biopsies were collected. Sections were stained with anti-PDL1 or H&E and scored by a molecular pathologist to generate CPS and Salgado TIL scores. Additional slides were stained with antibodies for CD3, CD8, CD56, CD19, FOXP3, cytokeratin, and DAPI. Whole slides were analyzed using CD3 and CD8 density to quantify infiltration. Single cell gene expression was measured using the 10x Genomics Single Cell 3’ Protocol. Sequencing was performed to a depth of at least 50,000 paired-end reads per cell. Cells were annotated using the Seurat and SingleR R packages. Correlation coefficients of immune cell infiltration estimates by the four methods were generated and visualized on scatter plots. Results: In evaluating immune cell infiltration, there was a moderate correlation between Salgado TIL scores and IHC with an R-squared value of 0.59. In evaluating T cell populations, CPS and scRNASeq did not correlate, with R-squared value of 0.0167. In our dataset, a higher CPS score was positively associated with platinum sensitivity. Conclusions: Single methodologies to estimate immune infiltration may not be sufficient to capture the complexity of the tumor microenvironment. Even though the correlation between methods was not high, it is possible that each method measures a different aspect of immune cell infiltration and the combination of methods may improve our ability to predict response to immunotherapies. Further analyses will be required to determine the biological properties that result in the different estimates. Immune cell infiltration is associated with positive ovarian cancer prognosis and is used to predict response to emerging immunotherapies. Multiple methods are used both clinically and in research to quantify immune infiltration, but there is a lack of consensus on the best method. The objective of this study was to compare four methods of measuring immune infiltration: immunohistochemistry for PDL1 (Combined Positive Score - CPS), H&E analysis of immune infiltration (Salgado TIL score), multiparameter immunofluorescence (IHC), and single cell RNA sequencing (scRNAseq). This exploratory work compares these four methods and calculates associations with disease outcomes. Thirty biopsies were collected. Sections were stained with anti-PDL1 or H&E and scored by a molecular pathologist to generate CPS and Salgado TIL scores. Additional slides were stained with antibodies for CD3, CD8, CD56, CD19, FOXP3, cytokeratin, and DAPI. Whole slides were analyzed using CD3 and CD8 density to quantify infiltration. Single cell gene expression was measured using the 10x Genomics Single Cell 3’ Protocol. Sequencing was performed to a depth of at least 50,000 paired-end reads per cell. Cells were annotated using the Seurat and SingleR R packages. Correlation coefficients of immune cell infiltration estimates by the four methods were generated and visualized on scatter plots. In evaluating immune cell infiltration, there was a moderate correlation between Salgado TIL scores and IHC with an R-squared value of 0.59. In evaluating T cell populations, CPS and scRNASeq did not correlate, with R-squared value of 0.0167. In our dataset, a higher CPS score was positively associated with platinum sensitivity. Single methodologies to estimate immune infiltration may not be sufficient to capture the complexity of the tumor microenvironment. Even though the correlation between methods was not high, it is possible that each method measures a different aspect of immune cell infiltration and the combination of methods may improve our ability to predict response to immunotherapies. Further analyses will be required to determine the biological properties that result in the different estimates.

Objectives: Chemotherapy resistance is a major cause of mortality in recurrent ovarian cancer. The goal of this study is to identify signaling pathways associated with chemotherapy resistance by analyzing gene expression in single cells from ovarian cancer specimens collected from women before and after platinum/taxane based neoadjuvant chemotherapy (NACT). Methods: Women were prospectively consented into our study and ovarian cancer tissue samples were collected from six patients with primary epithelial ovarian cancer both before and after administration of NACT. Samples were subjected to single cell RNA sequencing (scRNAseq) using the 10x Genomics platform followed by sequencing on an Illumina NovaSeq. Sequences were mapped to the human transcriptome and gene expression was quantified to produce unique molecular identifier counts for ~85,000 cells from the 12 samples. Unsupervised hierarchical clustering was performed using a shared nearest-neighbor graph based embedding algorithm implemented by the Seurat R package. Multiple annotation methods were used to assign cell types. Cells annotated as epithelial cancer cells for each sample were extracted and re-clustered and average gene expression was calculated for each pre-NACT cluster. To identify the pre-NACT cluster that had the highest similarity to the post-NACT cells, we performed Spearman Rank Correlation testing on each individual cell in the post-NACT sample comparing it to each cluster in the matched pre-NACT sample. The pre-NACT cluster with the highest number of matches to the post-NACT cells were considered the potential chemotherapy-resistant population in the pre-NACT sample, which we refer to as the ‘seeder’ cell cluster. We used multiple enrichment tests to identify signaling pathways activated in the seeder cell clusters compared to the other pre-NACT epithelial cell clusters. Results: We identified 62 genes that were significantly upregulated in the pre-NACT seeder cell clusters in at least 3 of 6 patient samples analyzed. Pathways enriched in this 62 gene set include 16 hallmark signaling pathways and 36 oncogenic signature pathways. In addition, transcription factor target enrichment identified 36 transcription factors based on the 62 gene set. Expected pathways included p53 and epithelial mesenchymal transition pathways. Novel pathways included TNFa, TGFb, JAK-STAT, interferon, and estrogen. Associated transcription factors included STAT3/5, SMAD4, and TP53. Conclusions: ScRNAseq analysis of matched pre- and post-NACT cancer samples identifies potential chemoresistant cells in pre-NACT samples capable of surviving NACT. The signaling pathways enriched in these cells represent potential therapeutic targets for selective elimination of these ‘seeder’ cells. Chemotherapy resistance is a major cause of mortality in recurrent ovarian cancer. The goal of this study is to identify signaling pathways associated with chemotherapy resistance by analyzing gene expression in single cells from ovarian cancer specimens collected from women before and after platinum/taxane based neoadjuvant chemotherapy (NACT). Women were prospectively consented into our study and ovarian cancer tissue samples were collected from six patients with primary epithelial ovarian cancer both before and after administration of NACT. Samples were subjected to single cell RNA sequencing (scRNAseq) using the 10x Genomics platform followed by sequencing on an Illumina NovaSeq. Sequences were mapped to the human transcriptome and gene expression was quantified to produce unique molecular identifier counts for ~85,000 cells from the 12 samples. Unsupervised hierarchical clustering was performed using a shared nearest-neighbor graph based embedding algorithm implemented by the Seurat R package. Multiple annotation methods were used to assign cell types. Cells annotated as epithelial cancer cells for each sample were extracted and re-clustered and average gene expression was calculated for each pre-NACT cluster. To identify the pre-NACT cluster that had the highest similarity to the post-NACT cells, we performed Spearman Rank Correlation testing on each individual cell in the post-NACT sample comparing it to each cluster in the matched pre-NACT sample. The pre-NACT cluster with the highest number of matches to the post-NACT cells were considered the potential chemotherapy-resistant population in the pre-NACT sample, which we refer to as the ‘seeder’ cell cluster. We used multiple enrichment tests to identify signaling pathways activated in the seeder cell clusters compared to the other pre-NACT epithelial cell clusters. We identified 62 genes that were significantly upregulated in the pre-NACT seeder cell clusters in at least 3 of 6 patient samples analyzed. Pathways enriched in this 62 gene set include 16 hallmark signaling pathways and 36 oncogenic signature pathways. In addition, transcription factor target enrichment identified 36 transcription factors based on the 62 gene set. Expected pathways included p53 and epithelial mesenchymal transition pathways. Novel pathways included TNFa, TGFb, JAK-STAT, interferon, and estrogen. Associated transcription factors included STAT3/5, SMAD4, and TP53. ScRNAseq analysis of matched pre- and post-NACT cancer samples identifies potential chemoresistant cells in pre-NACT samples capable of surviving NACT. The signaling pathways enriched in these cells represent potential therapeutic targets for selective elimination of these ‘seeder’ cells.