Neurodegenerative disease pathways are perturbed in patients with cancer who self-report cognitive changes and anxiety: A pathway impact analysis.

BACKGROUND: Cancer-related cognitive impairment (CRCI) and anxiety co-occur in patients with cancer. Little is known about mechanisms for the co-occurrence of these two symptoms. The purposes of this secondary analysis were to evaluate for perturbed pathways associated with the co-occurrence of self-reported CRCI and anxiety in patients with low versus high levels of these two symptoms and to identify potential mechanisms for the co-occurrence of CRCI and anxiety using biological processes common across any perturbed neurodegenerative disease pathways. METHODS: Patients completed the Attentional Function Index and the Spielberger State-Trait Anxiety Inventory six times over two cycles of chemotherapy. Based on findings from a previous latent profile analysis, patients were grouped into none versus both high levels of these symptoms. Gene expression was quantified, and pathway impact analyses were performed. Signaling pathways for evaluation were defined with the Kyoto Encyclopedia of Genes and Genomes database. RESULTS: A total of 451 patients had data available for analysis. Approximately 85.0% of patients were in the none class and 15.0% were in the both high class. Pathway impact analyses identified five perturbed pathways related to neurodegenerative diseases (i.e., amyotrophic lateral sclerosis, Huntington disease, Parkinson disease, prion disease, and pathways of neurodegeneration-multiple diseases). Apoptosis, mitochondrial dysfunction, oxidative stress, and endoplasmic reticulum stress were common biological processes across these pathways. CONCLUSIONS: This study is the first to describe perturbations in neurodegenerative disease pathways associated with CRCI and anxiety in patients receiving chemotherapy. These findings provide new insights into potential targets for the development of mechanistically based interventions.

Perturbations in inflammatory pathways are associated with shortness of breath profiles in oncology patients receiving chemotherapy.

PURPOSE: One plausible mechanistic hypothesis is the potential contribution of inflammatory mechanisms to shortness of breath. This study was aimed to evaluate for associations between the occurrence of shortness of breath and perturbations in inflammatory pathways. METHODS: Patients with cancer reported the occurrence of shortness of breath six times over two cycles of chemotherapy. Latent class analysis was used to identify subgroups of patients with distinct shortness of breath occurrence profiles (i.e., none (70.5%), decreasing (8.2%), increasing (7.8%), high (13.5%)). Using an extreme phenotype approach, whole transcriptome differential gene expression and pathway impact analyses were performed to evaluate for perturbed signaling pathways associated with shortness of breath between the none and high classes. Two independent samples (RNA-sequencing (n = 293) and microarray (n = 295) methodologies) were evaluated. Fisher's combined probability method was used to combine these results to obtain a global test of the null hypothesis. In addition, an unweighted knowledge network was created using the specific pathway maps to evaluate for interconnections among these pathways. RESULTS: Twenty-nine Kyoto Encyclopedia of Genes and Genomes inflammatory signaling pathways were perturbed. The mitogen-activated protein kinase signaling pathway node had the highest closeness, betweenness, and degree scores. In addition, five common respiratory disease-related pathways, that may share mechanisms with cancer-related shortness of breath, were perturbed. CONCLUSIONS: Findings provide preliminary support for the hypothesis that inflammation contribute to the occurrence of shortness of breath in patients with cancer. In addition, the mechanisms that underlie shortness of breath in oncology patients may be similar to other respiratory diseases.

Anxiety in oncology outpatients is associated with perturbations in pathways identified in anxiety focused network pharmacology research.

PURPOSE: Evaluate for perturbed signaling pathways associated with subgroups of patients with low versus high levels of state anxiety. These pathways were compared to the pathways identified across eight network pharmacology studies of the anxiolytic effect(s) of a variety of compounds. METHODS: Adult outpatients had a diagnosis of breast, gastrointestinal, gynecological, or lung cancer; had received chemotherapy within the preceding four weeks; and were scheduled to receive at least two additional cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct anxiety profiles based on Spielberger State Anxiety Inventory scores that were obtained six times over two cycles of chemotherapy. Blood samples were processed using RNA sequencing (i.e., RNA-seq sample, n = 244) and microarray (i.e., microarray sample; n = 256) technologies. Pathway perturbations were assessed using pathway impact analysis. Fisher's combined probability method was used to combine test results using a false discovery rate of 0.01. RESULTS: In the RNA-seq sample, 62.3% and 37.7% of the patients were in the low- and high-anxiety classes, respectively. In the microarray sample, 61.3% and 38.7% were in the low and high-anxiety classes, respectively. Forty-one perturbed signaling pathways were identified. Eight of these pathways were common to those identified in the network pharmacology studies. CONCLUSIONS: Findings increase our knowledge of the molecular mechanisms that underlie anxiety in patients receiving chemotherapy. This study provides initial insights into how anxiety in patients with cancer may share common mechanisms with anxiety in patients with other clinical conditions.

Perturbations in common and distinct inflammatory pathways associated with morning and evening fatigue in outpatients receiving chemotherapy.

BACKGROUND: Moderate to severe fatigue occurs in up to 94% of patients with cancer. Recent evidence suggests that morning and evening fatigue are distinct dimensions of physical fatigue. The purposes of this study were to evaluate the transcriptome for common and distinct perturbed inflammatory pathways in patients receiving chemotherapy who reported low versus high levels of morning or low versus high levels of evening cancer-related fatigue. METHODS: Patients completed questionnaires during the week prior to their chemotherapy treatment. Severity of morning and evening fatigue was evaluated using the Lee Fatigue Scale. Gene expression and pathway impact analyses (PIA) were performed in two independent samples using RNA-sequencing (n = 357) and microarray (n = 360). Patterns of interactions between and among these perturbed pathways were evaluated using a knowledge network (KN). RESULTS: Across the PIA, nine perturbed pathways (FDR < 0.025) were common to both morning and evening fatigue, six were distinct for morning fatigue, and four were distinct for evening fatigue. KN (19 nodes, 39 edges) identified the phosphatidylinositol 3-kinase (PI3K)-Akt pathway node (perturbed in evening fatigue) with the highest betweenness (0.255) and closeness (0.255) centrality indices. The next highest betweenness centrality indices were seen in pathways perturbed in evening fatigue (i.e., nuclear factor kappa B: 0.200, natural killer cell-mediated cytotoxicity: 0.178, mitogen-activated protein kinase: 0.175). CONCLUSIONS: This study describes perturbations in common and distinct inflammatory pathways associated with morning and/or evening fatigue. PI3K-Akt was identified as a bottleneck pathway. The analysis identified potential targets for therapeutic interventions for this common and devastating clinical problem.

Sleep disturbance is associated with perturbations in immune-inflammatory pathways in oncology outpatients undergoing chemotherapy.

OBJECTIVE/BACKGROUND: Sleep disturbance is a common problem in patients receiving chemotherapy. Purpose was to evaluate for perturbations in immune-inflammatory pathways between oncology patients with low versus very high levels of sleep disturbance. PATIENTS/METHODS: Sleep disturbance was evaluated using the General Sleep Disturbance Scale six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct sleep disturbance profiles. Pathway impact analyses were performed in two independent samples using gene expression data obtained from RNA sequencing (n = 198) and microarray (n = 162) technologies. Fisher's combined probability test was used to identify significantly perturbed pathways between Low versus Very High sleep disturbance classes. RESULTS: In the RNA sequencing and microarray samples, 59.1% and 51.9% of patients were in the Very High sleep disturbance class, respectively. Thirteen perturbed pathways were related to immune-inflammatory mechanisms (i.e., endocytosis, phagosome, antigen processing and presentation, natural killer cell mediated cytotoxicity, cytokine-cytokine receptor interaction, apoptosis, neutrophil extracellular trap formation, nucleotide-binding and oligomerization domain-like receptor signaling, Th17 cell differentiation, intestinal immune network for immunoglobulin A production, T-cell receptor signaling, complement and coagulation cascades, and tumor necrosis factor signaling). CONCLUSIONS: First study to identify perturbations in immune-inflammatory pathways associated with very high levels of sleep disturbance in oncology outpatients. Findings suggest that complex immune-inflammatory interactions underlie sleep disturbance.

Perturbations in Neuroinflammatory Pathways Are Associated With a Worst Pain Profile in Oncology Patients Receiving Chemotherapy.

Unrelieved pain occurs in 55% of cancer patients. Identification of molecular mechanisms for pain may provide insights into therapeutic targets. Purpose was to evaluate for perturbations in neuroinflammatory pathways between oncology patients with and without severe pain. Worst pain severity was rated using a 0 to 10 numeric rating scale six times over two cycles of chemotherapy. Latent profile analysis was used to identify subgroups of patients with distinct pain profiles. Pathway impact analyses were performed in two independent samples using gene expression data obtained from RNA sequencing (n = 192) and microarray (n = 197) technologies. Fisher's combined probability test was used to identify significantly perturbed pathways between None versus the Severe pain classes. In the RNA sequencing and microarray samples, 62.5% and 56.3% of patients were in the Severe pain class, respectively. Nine perturbed pathways were related to neuroinflammatory mechanisms (i.e., retrograde endocannabinoid signaling, gamma-aminobutyric acid synapse, glutamatergic synapse, Janus kinase-signal transducer and activator of transcription signaling, phagosome, complement and coagulation cascades, cytokine-cytokine receptor interaction, chemokine signaling, calcium signaling). First study to identify perturbations in neuroinflammatory pathways associated with severe pain in oncology outpatients. Findings suggest that complex neuroimmune interactions are involved in the maintenance of chronic pain conditions. Perspective: In this study that compared oncology patients with none versus severe pain, nine perturbed neuroinflammatory pathways were identified. Findings suggest that complex neuroimmune interactions are involved in the maintenance of persistent pain conditions.