Patient and Caregiver Perceptions of Advanced Bladder Cancer Systemic Treatments: Infodemiology Study Based on Social Media Data

Non-classic deubiquitinase USP13 inhibits bladder cancer metastasis through destabilizing cytoplasmic KDM3A

Bladder cancer (BLCa) metastasis is a predominant cause of death for bladder cancer patients. Histone demethylase KDM3A specifically removes the repressive mono- or di-methyl marks from H3K9 and thus contributes to the activation of gene transcription. However, the underlying mechanisms of KDM3A in bladder cancer are poorly understood. Here, we report that high levels of KDM3A are associated with bladder cancer clinical progression. KDM3A silencing inhibits bladder cancer cell growth, cell migration and invasion in vitro and in vivo. Mechanistically, we identify that non-classic deubiquitinase USP13 interacts with KDM3A to promote its degradation in cytoplasm via the proteasome-specific pathway. USP13 was significantly down-regulated in bladder cancer tissues and negatively associated with KDM3A expression. Furthermore, we show in bladder injected-liver metastasis xenograft model that USP13 inhibits bladder cancer metastasis through destabilizing cytoplasmic KDM3A. Collectively, our findings identify KDM3A is an important regulator of bladder cancer cell growth and metastasis and targeting USP13/KDM3A complex could be a valuable strategy to ameliorate bladder cancer progression and metastasis.

Perceptions in 3.6 Million Web-Based Posts of Online Communities on the Use of Cancer Immunotherapy: Data Mining Using BERTopic

BACKGROUND

Immunotherapy has become a game changer in cancer treatment. The internet has been used by patients as a platform to share personal experiences and seek medical guidance. Despite the increased utilization of immunotherapy in clinical practice, few studies have investigated the perceptions about its use by analyzing social media data.

OBJECTIVE

This study aims to use BERTopic (a topic modeling technique that is an extension of the Bidirectional Encoder Representation from Transformers machine learning model) to explore the perceptions of online cancer communities regarding immunotherapy.

METHODS

A total of 4.9 million posts were extracted from Facebook, Twitter, Reddit, and 16 online cancer-related forums. The textual data were preprocessed by natural language processing. BERTopic modeling was performed to identify topics from the posts. The effectiveness of isolating topics from the posts was evaluated using 3 metrics: topic diversity, coherence, and quality. Sentiment analysis was performed to determine the polarity of each topic and categorize them as positive or negative. Based on the topics generated through topic modeling, thematic analysis was conducted to identify themes associated with immunotherapy.

RESULTS

After data cleaning, 3.6 million posts remained for modeling. The highest overall topic quality achieved by BERTopic was 70.47% (topic diversity: 87.86%; topic coherence: 80.21%). BERTopic generated 14 topics related to the perceptions of immunotherapy. The sentiment score of around 0.3 across the 14 topics suggested generally positive sentiments toward immunotherapy within the online communities. Six themes were identified, primarily covering (1) hopeful prospects offered by immunotherapy, (2) perceived effectiveness of immunotherapy, (3) complementary therapies or self-treatments, (4) financial and mental impact of undergoing immunotherapy, (5) impact on lifestyle and time schedules, and (6) side effects due to treatment.

CONCLUSIONS

This study provides an overview of the multifaceted considerations essential for the application of immunotherapy as a therapeutic intervention. The topics and themes identified can serve as supporting information to facilitate physician-patient communication and the decision-making process. Furthermore, this study also demonstrates the effectiveness of BERTopic in analyzing large amounts of data to identify perceptions underlying social media and online communities.

Evaluating the caregiver experience during neoadjuvant therapy for pancreatic ductal adenocarcinoma

INTRODUCTION

Neoadjuvant therapy (NT) is increasingly recommended for patients with localized pancreatic ductal adenocarcinoma (PDAC). Recent research has highlighted the significant treatment burden that patients experience during NT, but caregiver well-being during NT is poorly understood.

METHODS

A cross-sectional mixed-methods analysis of primary caregivers of patients with localized PDAC receiving NT was undertaken. All patients completed the Caregiver Quality of Life Index-Cancer (CQOLC) survey, while semi-structured interviews were conducted among a convenience sample of participants.

RESULTS

Among 28 caregivers, the mean age was 60.1 years, and most were patient spouses/significant others (71.4%). Patients had resectable (18%), borderline resectable (46%), or locally advanced (36%) PDAC with a mean treatment duration of 2.9 months at the time of their caregiver's enrollment. Most caregivers felt that they received adequate emotional/psychosocial support (80%) and understood the rationale for NT (93%). A majority (60%) reported that caregiving responsibilities impacted their daily lives and required a decrease in their work hours, leading to financial challenges (47%). While overall QOL was moderate (mean 83 ± 21.1, range 0-140), "emotional burden" (47.3 ± 20.9), and "positive adaption" (57.3 ± 13.9) were the lowest ranked CQOLC subsection scores.

DISCUSSION

Caregivers of patients with PDAC undergoing NT experience significant emotional symptoms and impact on their daily lives. Assessing caregiver needs and providing resources during NT should be a priority.