Extracellular Vesicles-A Source of RNA Biomarkers for the Detection of Breast Cancer in Liquid Biopsies

Over the past decade, extracellular vesicles (EVs) have emerged as a promising source of cancer-derived RNAs for liquid biopsies. However, blood contains a pool of heterogeneous EVs released by a variety of cell types, making the identification of cancer RNA biomarkers challenging. Here, we performed deep sequencing of plasma EV RNA cargo in 32 patients with locally advanced breast cancer (BC) at diagnosis and 7 days after breast surgery and in 30 cancer-free healthy controls (HCs). To identify BC-derived RNA biomarkers, we searched for RNAs that had higher levels in BC EVs at the time of diagnosis compared with HCs and decreased after surgery. Data analysis showed that the fractions of miRNAs, snRNAs, snoRNAs, and tRFs were increased, but the fraction of lncRNAs was decreased in BC EVs as compared to HCs. BC-derived biomarker candidates were identified across various RNA biotypes. Considered individually, they had very high specificity but moderate sensitivity for the detection of BC, whereas a biomarker model composed of eight RNAs: SNORD3H, SNORD1C, SNORA74D, miR-224-5p, piR-32949, lnc-IFT-122-2, lnc-C9orf50-4, and lnc-FAM122C-3 was able to distinguish BC from HC EVs with an AUC of 0.902 (95% CI = 0.872-0.931, p = 3.4 × 10-9) in leave-one-out cross-validation. Furthermore, a number of RNA biomarkers were correlated with the ER and HER2 expression and additional biomarker models were created to predict hormone receptor and HER2 status. Overall, this study demonstrated that the RNA composition of plasma EVs is altered in BC patients and that they contain cancer-derived RNA biomarkers that can be used for BC detection and monitoring using liquid biopsies.

Comprehensive characterization of RNA cargo of extracellular vesicles in breast cancer patients undergoing neoadjuvant chemotherapy

Extracellular vesicles (EVs) are g7aining increased attention as carriers of cancer-derived molecules for liquid biopsies. Here, we studied the dynamics of EV levels in the plasma of breast cancer (BC) patients undergoing neoadjuvant chemotherapy (NAC) and explored the relevance of their RNA cargo for the prediction of patients' response to the therapy. EVs were isolated from serial blood samples collected at the time of diagnosis, at the end of NAC, and 7 days, 6, and 12 months after the surgery from 32 patients with locally advanced BC, and 30 cancer-free healthy controls (HCs) and quantified by nanoparticle tracking analysis. The pre-treatment levels of EVs in BC patients were higher than in HCs, significantly increased during the NAC and surgery, and decreased to the levels found in HCs 6 months after surgery, thus showing that a substantial fraction of plasma EVs in BC patients are produced due to the disease processes and treatment. RNA sequencing analysis revealed that the changes in the EV levels were associated with the alterations in the proportions of various RNA biotypes in EVs. To search for RNA biomarkers that predict response to the NAC, patients were dichotomized as responders and non-responders based on Miller-Payne grades and differential expression analyses were carried out between responders and non-responders, and HCs. This resulted in the identification of 6 miRNAs, 4 lncRNAs, and 1 snoRNA that had significantly higher levels in EVs from non-responders than responders at the time of diagnosis and throughout the NAC, and significantly lower levels in HCs, thus representing biomarkers for the prediction of response to NAC at the time of diagnosis. In addition, we found 14 RNAs representing piRNA, miRNA, lncRNA, snoRNA, and snRNA biotypes that were induced by NAC in non-responders and 2 snoRNAs and 1 piRNA that were induced by NAC in patients with early disease progression, thus warranting further functional studies on their role in chemoresistance and metastasis.

Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors

BACKGROUND

It is encouraging to see a substantial increase in individuals surviving cancer. Even more so since most of them will have a positive effect on society by returning to work. However, many cancer survivors have unmet needs, especially when it comes to improving their quality of life (QoL). Only few survivors are able to meet all of the recommendations regarding well-being and there is a body of evidence that cancer survivors' needs often remain neglected from health policy and national cancer control plans. This increases the impact of inequalities in cancer care and adds a dangerous component to it. The inequalities affect the individual survivor, their career, along with their relatives and society as a whole. The current study will evaluate the impact of the use of big data analytics and artificial intelligence on the self-efficacy of participants following intervention supported by digital tools. The secondary endpoints include evaluation of the impact of patient trajectories (from retrospective data) and patient gathered health data on prediction and improved intervention against possible secondary disease or negative outcomes (e.g. late toxicities, fatal events).

METHODS/DESIGN

The study is designed as a single-case experimental prospective study where each individual serves as its own control group with basal measurements obtained at the recruitment and subsequent measurements performed every 6 months during follow ups. The measurement will involve CASE-cancer, Patient Activation Measure and System Usability Scale. The study will involve 160 survivors (80 survivors of Breast Cancer and 80 survivors of Colorectal Cancer) from four countries, Belgium, Latvia, Slovenia, and Spain. The intervention will be implemented via a digital tool (mHealthApplication), collecting objective biomarkers (vital signs) and subjective biomarkers (PROs) with the support of a (embodied) conversational agent. Additionally, the Clinical Decision Support system (CDSS), including visualization of cohorts and trajectories will enable oncologists to personalize treatment for an efficient care plan and follow-up management.

DISCUSSION

We expect that cancer survivors will significantly increase their self-efficacy following the personalized intervention supported by the m-HealthApplication compared to control measurements at recruitment. We expect to observe improvement in healthy habits, disease self-management and self-perceived QoL. Trial registration ISRCTN97617326. https://doi.org/10.1186/ISRCTN97617326 . Original Registration Date: 26/03/2021.

Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors

Background

It is encouraging to see a substantial increase in individuals surviving cancer. Even more so since most of them will have a positive effect on society by returning to work. However, many cancer survivors have unmet needs, especially when it comes to improving their quality of life (QoL). Only few survivors are able to meet all of the recommendations regarding well-being and there is a body of evidence that cancer survivors’ needs often remain neglected from health policy and national cancer control plans. This increases the impact of inequalities in cancer care and adds a dangerous component to it. The inequalities affect the individual survivor, their career, along with their relatives and society as a whole. The current study will evaluate the impact of the use of big data analytics and artificial intelligence on the self-efficacy of participants following intervention supported by digital tools. The secondary endpoints include evaluation of the impact of patient trajectories (from retrospective data) and patient gathered health data on prediction and improved intervention against possible secondary disease or negative outcomes (e.g. late toxicities, fatal events).

Methods/design

The study is designed as a single-case experimental prospective study where each individual serves as its own control group with basal measurements obtained at the recruitment and subsequent measurements performed every 6 months during follow ups. The measurement will involve CASE-cancer, Patient Activation Measure and System Usability Scale. The study will involve 160 survivors (80 survivors of Breast Cancer and 80 survivors of Colorectal Cancer) from four countries, Belgium, Latvia, Slovenia, and Spain. The intervention will be implemented via a digital tool (mHealthApplication), collecting objective biomarkers (vital signs) and subjective biomarkers (PROs) with the support of a (embodied) conversational agent. Additionally, the Clinical Decision Support system (CDSS), including visualization of cohorts and trajectories will enable oncologists to personalize treatment for an efficient care plan and follow-up management.

Discussion

We expect that cancer survivors will significantly increase their self-efficacy following the personalized intervention supported by the m-HealthApplication compared to control measurements at recruitment. We expect to observe improvement in healthy habits, disease self-management and self-perceived QoL.

Trial registration ISRCTN97617326. https://doi.org/10.1186/ISRCTN97617326. Original Registration Date: 26/03/2021.

The impact of maximal strength training on quality of life among women with breast cancer undergoing treatment

Cancer rehabilitation programs mainly involve endurance cardio training while little attention has been paid to strength training. Breast cancer (BC) patients lose muscle strength while undergoing adjuvant treatment, thus affecting daily activities and quality of life. Maximal strength training, with an emphasis on velocity in the concentric phase, improves maximal strength and muscle force development characteristics. However, the effect of maximal strength training on quality of life for BC patients undergoing treatment remains elusive. Consequently, the aim of this study was to evaluate the effectiveness of maximal strength training in Health related quality of life in women with newly diagnosed BC.

MATERIALS AND METHODS

55 BC patients with disease stage I-III were randomized into a training group and control group. The training group performed maximal strength training twice a week for 3 months, whereas the control group followed prescribed treatment without strength training. Overall quality of life was measured by The European Organization for Research and Treatment of Cancer Core Quality of life Questionnaire-C30 and additional BC module BR23 before and after the intervention.

RESULTS

The results obtained from pre-tests and those obtained after 3 months of intervention revealed that patients in the training group significantly increased one repetion maximum, by 20.4 kg (20%) (p = 0.001, d = 0.9). Simultaneously, statistically significant alterations were observed in this variable for the control group, one repetition maximum decreased by 8.9 kg (9%) (p = 0.001, d = 0.5). The overall quality of life improved significantly by 13% for the training group with large effect (p = 0.002, d = 0.6), but no relevant changes were observed in the control group (p = 0.44, d = 0.2). Results revealed remarkable changes in overall quality of life after 3-month post-test period between the two groups with large effect (p = 0.002, d = 0.9). The training sessions had helped in diminishing the sense of fatigue by 24% (p = 0.03, d = 0.6), while it had got worse by 25% (p = 0.02, d = 0.4) for the control group. Again, the data on large effect were noticed to differ between the groups (p = 0.01, d = 0.6).

CONCLUSION

Maximal strength training for BC patients was well tolerated, safe and feasible and showed strength improvements that led to improved muscle strength and improved overall quality of life. These data certainly support the therapeutic role for maximal strength training in the treatment of BC.

Maximal Strength Training for Breast Cancer Patients Undergoing Adjuvant Treatment

Background: Breast cancer (BC) patients lose muscle strength during adjuvant treatment, thus affecting physical functioning. Maximal strength training (MST), with an emphasis on velocity in the concentric phase, improves maximal strength and walking efficiency. However, the effect of MST for BC patients undergoing treatment remains elusive. Aim: The aim of this study was to examine the feasibility and effects of such training in BC patients during clinical treatment on maximal muscle strength and functional performance. Methods: Thirty patients (46 ± 9 yr) with stage I-III BC were randomized to training group (TG) or control group (CG). TG performed MST twice a week for 3 months and CG followed prescribed BC treatment without strength training. TG performed four sets of four repetitions (4×4) of dynamic leg press with an emphasis on the maximal mobilization of force in the concentric action and with a progressively adjusted intensity corresponding to 85%–90% of one repetition maximum (1RM). Results: After the MST period, TG displayed significant 25 ± 7 kg (23%) increase in leg press 1RM ( P = 0.001). The strength improvements led to a significant increase in 6 minute walk distance (8%), 30-second chair test (23%), stair climb test (17%), and to a significant increase in walking performance of (8%) measured on an incremental treadmill test to exhaustion. In 3 months' posttest CG displayed significant 10 ± 8 kg (9%) decrease in 1RM ( P = 0.006). Reduced muscle strength leg to a significant decrease in 6 minute walk distance (6%), 30-second chair test (14%), stair climb test by (8%), and walking performance reduced significantly by (17%). Significant changes from pre to 3 months' posttest were observed between TG and CG in all functional performance measured variables. Conclusion: Maximal strength training was feasible during treatment and increased maximal muscle strength in BC patients. Increased strength led to improved functional performance after 24 training sessions each lasting only 20 min. Our results suggest that application of MST could accompany clinical training as a part of the treatment of BC patients. This training form showed excellent improvements in physical function tests and, thus should be implemented as a part of the breast cancer rehabilitation programs.

Extracellular Vesicles as Biomarkers and Therapeutic Targets in Breast Cancer

Cancer-derived extracellular vesicles (EVs) contain various cancer-associated molecules, such as mutated or overexpressed oncoproteins, glycoproteins, mRNAs, various non-coding RNAs and DNA fragments. They have been shown to propagate phenotypic traits, such as drug resistance, increased proliferation rate, invasiveness and stemness across cancer cells and to mediate cancer-induced immunosuppression. Therefore, cancer-derived EVs have gained increasing attention as cancer biomarkers and therapeutic targets. Unlike circulating tumor cells they are highly abundant in biofluids and, on the contrary to single-molecule circulating biomarkers, they protect their molecular cargo against degradation and may carry molecular signatures associated with specific phenotypes. Herein, we summarize studies investigating EVs as biomarkers in breast cancer and propose scenarios for various clinical applications of EV-based biomarkers in the management of breast cancer. Furthermore, we provide an overview of recent findings regarding the cancer-promoting effects of breast cancer-derived EVs and discuss opportunities for blocking EV-mediated signaling as a therapeutic strategy for breast cancer.

Prognostic relevance of carbonic anhydrase IX expression is distinct in various subtypes of breast cancer and its silencing suppresses self-renewal capacity of breast cancer cells

PURPOSE

Carbonic anhydrase IX (CAIX) is a hypoxia-inducible enzyme with extracellular catalytic domain that is overexpressed in a variety of cancers including breast cancer and plays a crucial role in maintaining favourable intracellular pH and reducing extracellular pH. The purpose of the current study was to elucidate the prognostic significance of CAIX in the intrinsic subtypes of breast cancer and to characterise CAIX as a drug target in breast cancer.

METHODS

The prognostic significance of CAIX mRNA expression was interrogated in a cohort of 3,455 breast tumours by using an online tool, Kaplan-Meier plotter. The functional effects of stable CAIX depletion by shRNA in three breast cancer cell lines—MDA-MB-231, MCF7 and SKBR-3, representing basal-like, luminal A and HER2+ subtypes, respectively—were studied by proliferation, invasion, clonal spheroid formation and chemosensitivity assays under normoxia and hypoxia. Finally, the effect of pharmacological CA inhibition alone or in the combination with doxorubicin on self-renewal was assessed by spheroid-forming assay.

RESULTS

High CAIX mRNA expression was significantly associated with poor survival in patients with basal-like, luminal B and triple-negative breast cancer, but not luminal A and HER+ subtypes. Silencing of CAIX expression had no significant effect on the cell proliferation or viability upon treatment with doxorubicin in any of the cell lines studied, while it inhibited spheroid formation in hypoxic conditions. Furthermore, pharmacological inhibition of CAs using acetazolamide had a synergistic effect with doxorubicin on decreasing the spheroid-forming efficiency in MDA-MB-231 cells.

CONCLUSIONS

Inhibition of CAIX reduces the self-renewal capacity of breast cancer cells, and the combination of doxorubicin and CAIX inhibition is an attractive therapeutic strategy in basal-like and triple-negative breast cancer, which warrants further investigations.