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| 2 | Peter Tang | -1 word(s) | 4085 | 2021-03-14 10:27:24 | | |
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Breast cancer (BC) is the most common cancer among women. Mortality is significantly raised due to drug resistance and metastasis, while personalized treatment options are obstructed by the limitations of conventional biopsy follow-up. Lately, research is focusing on circulating biomarkers as minimally invasive choices for diagnosis, prognosis and treatment monitoring. Circulating cell-free DNA (ccfDNA) is a promising liquid biopsy biomaterial of great potential as it is thought to mirror the tumor’s lifespan.
1. Introduction
Breast cancer (BC) remains in the very top of female oncology entities, with over 2 million new cases globally in 2018 [1]. BC is a heterogeneous disease of varying progression, while drug resistance and metastasis greatly reduce the survival rates. Current diagnostic/monitoring methods include mammography, ultrasound, tru-cut biopsy and ΜRI/CT scan. These techniques have several drawbacks (e.g., not suitable for all patients, low sensitivity and specificity, invasive and expensive).
Circulating biomarkers have been gaining ground as easy, minimally invasive choices for disease follow-up. The carcinogenic antigen CA 15-3 remains the “gold standard” for disease and therapy monitoring, although inadequate in sensitivity and specificity [2][3]. The FDA has recently approved the CellSearch system for measuring circulating cancer cells (CTCs), but only in metastatic disease [4][5]. Also, Oncotype DX, a 21-gene transcript-based assay, is currently used as a prognostic tool and for personalized treatment options in early stage ER + BC [6]. As an alternative, ccfDNA is currently the spearhead in biomedical research and provides the choice of non-invasive repetitive sampling for cancer monitoring. However, still limited clinical implementation [7], while a better understanding of its biology is expected to create an opportunity for its optimal exploitation in clinical routine. In the present review, we summarize the growing evidence that support this view, focusing in data specific for BC. Besides articles referring to ccfDNA, we also include findings from studies from other circulating complexes that contribute to the ‘pool’ of the ccfDNA, such as nucleosomes, vitrosomes and extracellular vesicles. Aberrant genetic alternations detected in ccfDNA are omitted, as thoroughly recently reviewed elsewhere [8][9].
2. Liquid Biopsy
During the life span of a tumor, cancer cells change constantly, acquiring genetic and epigenetic modifications and forming clones with different survival advantage resulting in the heterogeneity of cancer cell population [10][11]. The idea of discovering tools depicting these changes and monitoring them in «real time» is of obvious importance. Liquid biopsy is a minimally invasive approach in oncology, using peripheral blood as a source of biological material escaping the tumor and enriching circulation, such as ccfDNA, circulating tumor cells (CTCs) or extracellular vesicles (EVs) and platelets, assuming that they carry identical molecular characteristics of the parental tumor [12][13]. Liquid biopsies could reflect the heterogeneity of a primary tumor or the molecular evolution of a distant metastatic lesion, which is impossible using the conventional tissue biopsies. Another significant advantage is that upon sequential sampling due to its minimally invasive nature, it is possible to dynamically monitor disease and drug resistance acquisition. This approach could therefore offer a powerful tool in the field of clinical oncology of recognized value [14][15]. The initial steps on its actual implementation in clinical practice are taken and are expected to move forward longitudinally in the starting decade.
3. Circulating Cell-Free DNA
The first demonstration of circulating DNA in the bloodstream of healthy individuals was done by Mendel and Métais in 1948 [16]. Thirty years later, it was shown that the concentration of ccfDNA from cancer patients is greater than that from healthy individuals [17]. In 1989, Stroun et al. identified fragments of circulating DNA originating from cancer cells in the bloodstream, based on a technique that identified decreased strand stability [18]. These hallmarks brought circulating DNA in the center of the biomarker discovery field to aid precision medicine.
ccfDNA is DNA liberated from cells into biological fluids, e.g., blood, lymph, bile, milk, urine, saliva, mucous suspension, spinal fluid [19]. It is double or single stranded and can be either of nuclear or mitochondrial origin. In health, ccfDNA is mainly released from cells like hematopoietic, whereas in disease, it is enriched also from pathological tissues. Cancerous ccfDNA is called circulating tumor DNA (ctDNA) and represents only a fraction of the total ccfDNA in the blood [20]. ctDNA is liberated from tumor cells, metastatic sites and CTCs and it has been proved to reflect dynamically the genetic and epigenetic events in the tumor’s lifetime [21]. The detection of mutations, Loss of heterogeneity (LOH) and aberrant methylation is considered a mean of identification of the ctDNA fraction and could serve as diagnostic/prognostic/predictive indicators [14][22][23]. Minimally invasive consecutive sampling might therefore represent dynamically genetic and epigenetic characteristics of the tumor presenting a clear advantage over established biomarkers.
4. Methylation of ccfDNA
DNA methylation is defined as the covalent addition of a methyl group at the 5-carbon of the cytosine ring by DNA methyltransferases (DNMTs), mostly within CpG dinucleotides [24]. It is a well-defined epigenetic mechanism contributing to gene expression regulation [25]. DNA methylation is related to a variety of normal functions [24][26]. Also, promoter methylation of susceptible genes is associated with cancer [27][28][29] as well as hypomethylation [30] and their evaluation has been suggested as a potential clinical biomarker [31][32]. ccfDNA released from tumor cells has been shown to retain its epigenetic features [33][34]. Studies in multiple types of solid tumors have investigated the methylation profile of ccfDNA to evaluate its diagnostic, prognostic and predictive potential and add in their clinical management [14][22]. In breast cancer, the first documentation of aberrant methylation of ccfDNA was by Silva JM et al., in 1999, detecting the methylation of P16INK4A in plasma and in the corresponding tumor, indicating its cancer origin [35]. Since then, many studies reviewed below, have been performed to evaluate liquid methylation biomarkers in breast cancer associated with different clinical endpoints (Table 1). They differ significantly in the pre-analytical protocols for ccfDNA isolation as well as the methodology adopted for methylation detection assays and are often limited in a small cohort, still they accumulatively show that there is valuable information there awaiting further exploitation.
Table 1. Summary of studies evaluating ccfDNA methylation in BC diagnosis, prognosis and treatment response.
|
Table |
Study Group |
Clinical End-Point |
Findings |
References |
|---|---|---|---|---|
|
Diagnostic Biomarkers |
||||
|
P16INK4A |
- 35 BC patients |
Tumor-related origin of ccfDNA |
[35] |
|
|
HIC-1, RARβ2, RASSF1A |
|
BC diagnosis |
RARβ2 and RASSF1A methylation in combination with ccfDNA quantitative analysis could discriminate malignant from non-malignant disease. |
[36] |
|
gene panel |
|
BC diagnosis |
ITIH5, DKK3, and RASSF1A methylation was correlated to early diagnosis |
[37] |
|
CST6 |
|
clinicopathological parameters and outcome |
CST6 is highly methylated in BC ccfDNA and could serve as biomarker |
[38] |
|
BRCA1, MGMT, GSTP1 |
|
clinicopathological parameters and prognosis (DFS, OS) |
Concordance between tumor and ccfDNA methylation of BRCA1, MGMT, GSTP1, correlation between MGMT protein loss and promoter hypermethylation, prognostic value of BRCA1,GSTP1 methylation in ccfDNA |
[39] |
|
Gene panel |
|
clinicopathological parameters and outcome(DFS, DSS), diagnosis |
Diagnostic value of APC, FOXA1 and RASSF1A methylation of ccfDNA in BC (over 70% sensitivity, specificity) |
[40] |
|
Gene panel |
|
Diagnosis of BC, CC and LC, correlation to clinical parametes |
«PanCancer» panel (APC, FOXA1, RASSF1A) for detecting cancer (72% sensitivity and 74% specificity) and «CancerType» panel (SCGB3A1, SEPT9, SOX17) indicating cancer topography (over 80% specificity), RASSF1A and RARβ2 methylation correlated to clinical parameters in BC |
[41] |
|
Gene panel |
|
BC diagnosis |
EGFR, PPM1E and 8 gene-specific CpG sites were significantly hypermethylated in BC with sufficient performance for breast cancer detection (AUC 0.66 TO 0.75) |
[42] |
|
Methylation array |
|
BC diagnosis |
CancerLocator tool for determining presence and location of BC |
[43] |
|
9223 CpG sites |
|
BC diagnosis, prognosis (OS), response to treatment (TTF) |
Methylation scores could detect BC and classify the underlying cancer type with high accuracy (91.7% and 72.7% respectively), low methylation scores were associated with longer OS |
[44] |
|
Prognostic Biomarkers |
||||
|
Gene panel |
- 101 BC women |
Prognosis (OS, DFS), correlation to clinicopathological parameters |
High methylation of seven genes was correlated to poor prognosis, Methylation of p16INK4A, BRCA1, GSTP1, PRB and RARβ2 were associated with unfavorable clinical parameters |
[45] |
|
ESR1 |
- 110 BC women |
Correlation to clinicopathological parameters |
High methylation of ESR1 was associated with ER negative receptor status and phenotypes with poor prognosis and could predict treatment response. |
[46] |
|
GSTP1, RASSF1A, RARβ2 |
- 336 ΒC women |
Correlation to clinicopathological parameters, prognosis (OS, DFS) |
Positive methylation of at least one of the three genes and high ccfDNA levels were associated with worse DFS and OS |
[47] |
|
GSTP1, RASSF1A, RARβ2 |
- 120 BC women |
Correlation to clinicopathological parameters, prognosis (OS, DFS) and response to treatment |
Positive methylation of at least one of the three genes and high ccfDNA levels were associated with worse DFS and OS and no response to treatment |
[48] |
|
Six BC specific DNAme patterns |
|
Prognosis (OS, DFS) and response to treatment |
EFC#93 serum DNAme positivity was a poor prognostic factor and correlated to response to anti-hormonal treatment |
[49] |
|
Gene panel |
|
BC diagnosis, prognosis (OS, DFS) and treatment response |
Methylation of SOX17, WNT5A, KLK10 was correlated to poor prognosis and two specific classifiers were constructed for prognosis of patients with metastatic BC (AUC 0.737). Another classifier could sufficiently discriminate BC disease (AUC 0.844). Positive methylation of at least 4 of any studied gene was correlated to the absence of chemotherapy response |
[50] |
|
Predictive Biomarkers |
||||
|
Gene panel |
|
Neoadjuvant treatment response, correlation to clinicopathological parameters |
BRCA1 methylation status discriminate responders from non-responders |
[51] |
|
RASSF1A |
|
Correlation to clinicopathological parameters, monitoring of adjuvant tamoxifen therapy response, prognosis (OS, DFS) |
Methylation of RASSFIA was correlated to poor prognosis and resistance in tamoxifen treatment |
[52] |
|
ESR1, STRATIFIN |
- 111 BC patients |
Development of metastasis, response to treatment |
Methylation of STRATIFIN could discriminate metastatic BC patients form those who were cancer free and was associated to treatment response (75% sensitivity and 66.7% specificity) |
[53] |
|
Gene panel |
- 20 BC patients (sequential sampling) |
Treatment monitoring |
Methylation of PR, PROX, MDGI, PAX 5 and RARβ2 was diminished after surgery, especially in the combined treatment group (surgery and tamoxifen treatment). Surgery alone decreased methylation in PAX5 and RARβ2, while tamoxifen treatment changed ESR1 methylation |
[54] |
|
Gene panel (cMethDNA) |
|
Treatment response |
Cancer-specific methylated DNA was detected in recurrent stage ΙV BC patients (91% sensitivity and 96%specificity) and cMethDNA assay could reflect treatment response |
[55] |
|
Whole-genome bisulfite sequencing |
|
Prediction of recurrence |
Identification of 21 DNA hypermethylation hotspots associated with metastatic BC. |
[56] |
BC = Breast Cancer; CC = Colon Cancer; ccfDNA = circulating cell-free DNA; DFS = Disease Free Survival; DSS = Disease Specific Survival; LC = Lung Cancer; MBC = Metastatic Breast Cancer; NSCLC = Non-Small Cell Lung-Cancer; OS = Overall Survival; TTF = Time to Treatment Failure.
5. Hypomethylation in Breast Cancer
Breast cancer cells are highly hypomethylated [57][58][59] and global hypomethylation is correlated to clinicopathological characteristics of breast lesions [59]. A possible mechanism for DNA methylation loss in BC is through the formation of repressive chromatin at partially methylated domains (PMD) [60]. A recent study in BC reported that hypomethylation in PMD occurs in large fractions of the genome that display genetic and epigenetic alterations [61]. Only a few studies have investigated global hypomethylation of ccfDNA in BC. Genome-wide approaches have proved that ccfDNA is hypomethylated in metastatic breast cancer (MBC) [56][62]. Global hypomethylation was also detected in the plasma of BC patients by massively parallel bisulfite sequencing, which could be an attractive approach for diagnosis and disease monitoring [63].
6. Other Parameters of ccfDNA in Breast Cancer
The research on the development of ccfDNA-based biomarkers in cancer is not limited to the analysis of its sequence for identifying alterations (DNA methylation, mutations, LOH, etc.). Below, we present data from the study of other parameters such as quantity, protein content, integrity, release mechanism, etc. important features that could lead to the development of multi-parametric prognostic and predictive biomarkers in BC.
6.1. Quantity of ccfDNA
As aforementioned, small quantities of ccfDNA are detected in the plasma/serum of healthy individuals, but its concentration is notably increased in cancer or other pathological conditions [64][65]. The quantity of tumor-derived ccfDNA in the bloodstream differs and depends on tumor size and cancer type (blood-barrier in brain tumors). Also, it has been mentioned that DNAase activity often impaired in cancer patients is correlated to ccfDNA concentrations [66]. Clearance rates in liver, spleen, kidney and to a less extend degradation from blood nucleases are additional factors affecting quantity [67][68][69], while the half-life of ccfDNA could last from 15 min to a couple of hours [19].
Besides other characteristics, quantity of ccfDNA is by itself a parameter with potential value for diagnosis, classification and treatment monitoring. Several techniques have been proposed for total ccfDNA level measurements in blood, either direct in unpurified plasma [50][70][71] or after DNA isolation [72][73]. In our recent work in BC, we measured ccfDNA quantity directly, using a SYBR Green-based/Qubit assay; it is important to note that by this method, only free unbound ccfDNA is measured, as assay SYBR Green dye can only bind to free/naked DNA. In contrast, after isolation, all ccfDNA (naked, bound in nucleosomes, proteins or internalized in vesicles) is extracted and measured. The techniques mostly used so far for ccfDNA quantification is quantitative PCR (qPCR) in BC for the short and long sequences ALU115/247 [74][75] and LINE1 sequences [76] or using the reference gene GAPDH [77][78]. Both methods have repetitively confirmed higher ccfDNA levels in BC in relation to healthy individuals [73][75][76][78][79][80][81][82][83][84][85][86][87]. Increased levels of ccfDNA in BC have also been correlated to metastasis [50][75][80], tumor size [73][76][77][78], other histopathological parameters [73][83] and BC outcome [50][84]. In our recent study, elevated levels of ccfDNA were correlated to the incidence of death, shorter PFS and non-response to pharmacotherapy in metastatic patients [50]. Most interestingly from a clinical aspect is the construction of a single-parametric linear model using ccfDNA plasma concentration values with great discriminating power to predict response to chemotherapy [50]. However, in our patient group we did not detect correlations of quantity to clinicopathological parameters, possibly due to the different quantification methods and patient classification criteria, in concordance with some researchers [80][82]. Other studies have assessed the ccfDNA quantity in relation to diagnosis. In a study, researchers developed a qPCR assay using telomere, centromere and LINE primers and showed that the shortening of telomeric ccfDNA in plasma was correlated to BC [88]. The circulating levels of the longer fragment of ALU247 have also been shown to hold a diagnostic potential, shown to discriminate the cancer from non-cancer subjects [81]. Also, it has been shown that ccfDNA was superior to other circulating biomarkers in detecting BC. it has been found that ccfDNA as measured by qPCR for the GAPDH gene, was superior to serum vascular endothelial growth factor measured by ELISA in discriminating healthy from BC women [89]. A study in MBC showed that ccfDNA was superior to CTCs or CA 15-3 for disease monitoring, as levels showed greater correlation with changes in tumor burden and detected earlier than CA 15-3 or CTCs treatment response [90], proving its superiority over other innovative or established circulating biomarkers. This was further confirmed by studies using ALU and LINE1 levels to quantify ccfDNA [91][92]. It was earlier proposed that cancerous ccfDNA fragment measurements could serve as a reliable tool to monitor tumor dynamics in the course of disease and therapy [15] and indeed a recent meta-analysis of 13 studies concluded that the concentration of ccfDNA had great sensitivity and specificity [87% (95% CI, 73–94%) and 87% (95% CI, 79–93%), respectively] for BC diagnosis [93]. Furthermore, Catarino et al. using a real-time PCR probe assay for the hTERT gene, quantified ccfDNA of BC patients before and after surgery. They showed that ccfDNA levels were significantly decreased after surgery, successfully reflecting the tumor removal [79]. In accordance to that, Agassi et al. used a SYBR Gold-based fluorescence assay for ccfDNA quantification and confirmed that ccfDNA quantity was diminished after tumor resection [94]. Recently, researchers using the same quantification technique found that the reduction of ccfDNA levels were correlated to surgical removal or tumor reduction by chemotherapy, confirming once again previous studies. However, in the same study ccfDNA levels could not discriminate between patients with BC and healthy individuals for diagnostic purposes [95]. Maybe this discrepancy could be attributed to the use of the SYBR Gold-technique for ccfDNA quantification which can be quite sensitive, but lacks in specificity due to RNA interference. Very recently, Moss et al. compared genome wide methylation data of different tissues and cell types and found a breast-unique methylation pattern of three genes (znf296, krt19, lmx1b) which was used to quantify breast derived-ccfDNA in plasma using massive parallel sequencing. This approach could sufficiently discriminate between healthy individuals and cancer patients (AUC: 90.44% (95% CI: 78.51%–100%)), while no breast molecules were identified in healthy individuals. Also, breast derived-cfDNA levels were associated with tumor aggressiveness and a decrease was noticed during neo-adjuvant treatment. Notably, the persistent presence of breast derived-ccfDΝA after treatment indicated the existence of minimal residual disease [96]. This is an excellent proof showing that the tissue specificity of methylation could precisely reflect and monitor tumor burden. A more sophisticated approach for optimal feature selection such as automated machine learning would be a more appropriate methodological choice to deliver tissue specific signatures.
Obviously, high levels of ccfDNA in the bloodstream could be due to the presence of a solid tumor but could also be related to other pathologies such as autoimmune disorders, inflammation and others. Hence, ccfDNA concentration can be proposed to serve diagnostic proposes in BC or reflecting removal of a primary breast tumor only adjunct to other tissue of origin or cancer related markers and clinical manifestations. On the other hand, due to its high sensitivity in MBC and in predicting treatment response [50][90], it could be envisaged to offer a reliable and simple solution for treatment monitoring. Validation in a clinical setting is highly anticipated to speed up application.
6.2. Integrity of ccfDNA
In 1989, Stroun et al. showed that ccfDNA of cancer patients is shorter than the ccfDNA of healthy individuals [18] implying that the study of ccfDNA integrity could aid the discrimination of cancerous ccfDNA from total ccfDNA but also biomarker discovery. Many studies have been conducted analyzing ccfDNA Integrity (cfDI) as the ratio between longer and shorter DNA fragments, with controversial findings so far. The most widely used method for cfDI assessment is the measurement of non-coding DNA integrity, such as repetitive elements ALU and LINE. In a 2006 study, researchers using the ALU247/ALU115 ratio found that patients having breast cancer of stage I, II and III showed greater integrity of ccfDNA as compared to healthy individuals [83]. Similarly, Iqbal et al. showed that ALU247/ALU115 was higher in stage IV breast cancer than in earlier stages and declined after surgery, suggesting it as a clinically relevant prognostic biomarker [84]. Kamel et al. found that cfDI was significantly higher in breast cancer than in benign breast patients and healthy individuals, using different amplicons of β-actin and was correlated to TNM stage [97]. Similar studies have been conducted in breast cancer and other cancer types confirming the finding that cfDI is greater in cancer [83][87][98][99].
These results however were not confirmed by several other studies, showing in contrast that healthy individuals showed greater cfDI than BC patients. Madhavan et al. suggested that it is the reduced cfDI that can serve as diagnostic marker for primary and metastatic breast cancer [100]. In a later study, researchers using the long and short fragment of HER2, MYC, BCAS1 and PI3KCA genes showed that BC patients had lower integrity than healthy individuals [85]. Cheng et al. using the ALU/LINE1 method proved that in BC the cfDI was significantly lower in recurrent patients, discriminating them from the non-recurrent patients [101]. Also, the same researchers reported that MBC patients showed increased cfDI after the first cycle of therapy and that it can be an independent prognostic marker [91] in contrast to earlier findings showing that the distribution of the cfDI in BC patients did not change after adjuvant chemotherapy [102]. Both Cheng’s and Madhavan’s studies used greater BC cohorts [100][101] than previous studies [83], adding to the power of their findings, however this controversial matter needs further elucidation.
Massive parallel sequencing added considerable to the deeper understanding of ccfDNA integrity. Jiang et al. proved that fragments originating from cancer cells were smaller than the fragments from healthy cells in patients with hepatocellular carcinoma. In the same study, patients having greater quantity of cancerous ccfDNA had a more fragmented DNA profile [103], in concordance with two previous studies in metastatic colorectal cancer [104] and pancreatic cancer [105]. In our BC study, we showed via capillary electrophoresis that patients at advanced stage that started neo-adjuvant or first line therapy had fragments sized from 22 to 160 bp, whereas this pattern was not observed in healthy individuals. We also showed that patients with higher total levels of ccfDNA had a greater number of short fragments (<160 bp). Finally, tumor size and the incidence of death were correlated with greater DNA fragmentation [50]. We assume that the pattern of fragments (22 to 160 bp) that we found in advanced BC is the result of degradation after ccfDNA liberation during cell death or active release. Most recently, researchers used a genome-wide approach for analyzing the fragmentation patterns of ccfDNA for early detection of BC and six different cancer types (DELFI study). They found that healthy individual ccfDNA patterns were correlated to nucleosomal DNA fragments originating from lymphocytes, while cancer patient fragmentation patterns were more variable, with shorter median overall length, in concordance with our findings. Most interestingly, using the DELFI approach they could recognize with high sensitivity a specific cancer type among others [106].
cFDI assessment could have a clinical application, although there is still discrepancy between researchers, some claiming that longer fragments represent the tumorous DNA while others the opposite. We assume that the main reason for these controversial findings is the selection of different methods for measuring cfDI (ALU247/ALU115 vs. others), as different fragments are quantified. Other reasons possibly depend on the differences in studied patient groups, with varying disease stage representation. Tumor growth kinetics may cause significant differences in the cellular release of ccfDNA and degradation. The pre-analytical process chosen in each study might as well represent a source of discrepancy, as shown in a study comparing different extraction methods of ccfDNA from plasma (phenol-chloroform isoamyl vs. QIAamp DNA Blood Mini Kit) that found different fragment lengths in the elutant of each method [71]. Despite the fact that ccfDNA is systematically investigated, until now different groups have not agreed to a standard operational pre-analytical procedure (e.g., sample collection, DNA extraction method), leading to variations and often in opposite findings between studies. In conclusion, for valid conclusions drawn from ccfDNA integrity studies, but also in general, it is important for the different methods to be compared in the same cohort of samples, as well as the establishment of a widely-accepted pre-analytical procedure.
6.3. ccfDNA Releasing Mechanism
Both apoptosis [107] and necrosis [65] have been suggested as mechanisms of cellular release of ccfDNA, whereas active release from viable cells [108] has also been described. Different ways of cell death are also sources of ccfDNA. For example, macrophages which engulf and degradate necrotic and apoptotic cells liberate degraded DNA [109]. An ischemic cell death (oncosis) has also been described in cancer [110] and could alternatively release DNA fragments. ccfDNA of 166 bp or multiples (single, di-, tri- and polynucleosomes) is possibly released through apoptosis and is the result of the action of a caspase-dependent endonuclease that cleaves DNA between nucleosomes. It is more or less accepted that the larger fraction of ccfDNA in human plasma is produced via apoptosis [ 109], fragments sized 10,000 or bigger derive from necrosis, while active release delivers a fragments of 2000 bp [111][112], although it is clear that the exact pathways of ccfDNA production in each case still needs to be clarified. Our study evaluated fragment size distribution by capillary electrophoresis and showed all above types of fragments (160 bp, 2000 bp and 10,000 bp) present in the plasma of BC patients, indicating all three releasing mechanisms (apoptosis, active release and necrosis) responsible for the liberation of ccfDNA [50]. This was further confirmed by our in vitro studies using the human breast cancer cell line MCF-7, where fragment—size profiling was indicative of active release, whereas exposure to the demethylating agent 5—AZA—CR induced the release of additional shorter fragments, indicative of apoptosis (see below) [34].
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