The Role of Long Non-coding RNA (NKILA and LINC00993) as Tumour Biomarkers in Breast Cancer

doi:10.21203/rs.3.rs-3981829/v1

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The Role of Long Non-coding RNA (NKILA and LINC00993) as Tumour Biomarkers in Breast Cancer

https://doi.org/10.21203/rs.3.rs-3981829/v1

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Background

Breast cancer) BC) is the most frequent cancer among women and the second most common cause of cancer deaths worldwide. Long non-coding RNAs (NKILA and LINC00993) are downregulated in BC and can have potential use as a novel tumor biomarker.

Aim of the work:

To investigate the Long non-coding RNA (NKILA and LINC00993) and cytokines (NF-KB and CXCL-1) as potential biomarkers in breast cancer.

Subjects and methods:

This case-control study included sixty-four pairs of surgically resected human breast cancer tissues and adjacent breast tissues. Expressions of LncRNAs (NKILA, LINC00993) and (NFκB, CXCL1) cytokines were detected using real-time quantitative polymerase chain reaction (qPCR) analysis,

Results

There was a significant decrease in LncRNAs (NKILA, LINC00993) levels in tumor tissue compared to normal tissue (P < 0.001). Also, there was a significant increase in NF-KP and CXCL1 levels in tumor tissue compared to normal tissue (P < 0.001). ROC curve analysis indicated that the LncRNAs (NKILA, LINC00993) expression levels could be considered a promising marker for the diagnosis of breast cancer patients with a sensitivity (90.6%, 92.2% respectively). Also, cytokines (NF-KB and CXCL-1) expression levels could be considered a promising marker for the diagnosis of breast cancer patients with a sensitivity and specificity of 87.5%, 89.1% respectively).

Conclusion

These findings suggest that LncRNAs (NKILA, LINC00993) and cytokines (NF-KB and CXCL-1) can be used as novel biomarkers for breast cancer.

Biomarker

NKILA

LINC00993

breast cancer

Breast cancer (BC) has become one of the most common malignant tumour, and the incidence rate is increasing every year [1]. The incidence is significantly higher in developed countries than in developing countries [2]. In Egypt, BC is estimated to be the most common cancer among females (37.7%) and the leading cause of death (29.1%). The mechanism of breast carcinogenesis is still not fully understood [3].

Early diagnosis of cancer remains a challenge for clinicians; it is an important goal to reduce treatment-associated morbidity and mortality and to reach maximal long-term survival [4].

Long non-coding RNAs (lncRNAs), which are RNA transcripts with a length greater than 200 nucleotides, have exhibited oncogenic or tumour suppressive roles in the pathogenesis of breast cancer [5, 6]. NF-κB Interacting LncRNA (NKILA) can be involved in the pathogenesis of a wide spectrum of human disorders. Numerous studies in hepatocellular carcinoma, breast cancer, melanoma, glioma, and other types of neoplasms have indicated the role of NKILA in the blockage of tumor growth and inhibition of metastasis [7].

LINC00993 (Long intergenic non-protein coding RNA 00993) is located on chromosome 10 and considerably downregulated in Triple Negative Breast Cancer (TNBC) and associated with Estrogen Receptor (ER) expression [8]. To the best of our knowledge, the precise relationship between NKILA and LINC00993 and breast cancer remains poorly understood.

NKILA has inhibitory roles on NF-κB which belongs to a family of transcription factors that regulate expression of several molecules and cytokines as C-X-C motif chemokine ligand 1 (CXCL1) participating in various crucial physiological reaction including immune responses, cell proliferation and differentiation, as well as cell death [9].

This work aims to investigate the Long non-coding RNA (NKILA and LINC00993) and cytokines (NF-KB and CXCL-1) as a potential biomarkers in breast cancer.

The study included Sixty-four patients with primary breast cancer who attended the General Surgery Department, at Zagazig University Hospital for partial/total mastectomy. The age of the studied participants ranged between 40 to 66 years with a mean of 52.75 years. 57.8% had a positive family history.

Sixty-four tissue samples were obtained from tumor tissues represent group A or the case group, and sixty-four tissue samples from their normal adjacent tissues as controls serving as the control group or group B.

This case-control study has been approved by the Ethical Committee of the Faculty of Medicine, Zagazig University, and following the Helsinki Declaration of 2013. All patients were subjected to full history taking and a complete general examination. The diagnosis of all patients was pathologically confirmed after positive mammography.

Sample collection and RNA Isolation

The sixty-four pairs of surgically resected breast tissues were immediately frozen and kept at − 80°C. Homogenization of cancer breast tissues was performed using a power homogenizer. GENEzol™ Reagent, TriRNA Pure Kit, (Geneaid, China) was used for RNA extraction.

Conversion of RNA into cDNA (complementary DNA)

RNA was reverse transcribed using a Maxime RT PreMix kit according to the manufacturer’s instructions. cDNA samples were stored undiluted at − 80°C.

Real-Time RT-PCR

The real-time RT-PCR was performed in a Rotor-Gene Q 2 plex Real-Time PCR System (Qiagen, Germany) using TopReal sybergreen master mix (Enzynomics, Korea). The primer sequences used for qRT-PCR are shown in (Table 1). The relative expression was calculated with 2^−ΔΔct method [10].

Statistical Analysis

Data were analysed using SPSS version 22, and data were expressed as mean ± SD for quantitative parametric variable, median for non-parametric one, categorical variable expressed as frequency and percentage, Student’s t test, and Mann-Whitney were used when appropriate. p < 0.05 was considered statistically significant. The analysis was based on the accuracy of the identified LncRNA (NKILA and LINC00993) and cytokines (NF-KP and CXCL-1) as a potential biomarker in breast cancer using receiver operator characteristic (ROC) curves as area under the curve (AUC) value and sensitivity and specificity.

There was a significant decrease in LncRNA (NKILA and LINC00993) in tumour tissue compared to normal tissue (P < 0.001). There was a significant increase in NF-KP and CXCL-1 in tumour tissues compared to normal tissue (P < 0.001) (Table 2).

There was a significant decrease in NKILA in cases with positive family history, Grade 3, negative ER and PR, and N3 compared to other cases (P < 0.001). Also, there was a significant decrease in LINC00993 in cases with Grade 3 and N3 compared to other cases (P < 0.001). There was a significant increase in NF-KB in cases with negative Er, PR, and N3 compared to other cases. Also, there was a significant increase in CXCL-1 in cases with tumour size > 5, ILC type, grade 3, and T3 or 4 compared to other cases. (Table 3)

There was a positive correlation between LINC00993, NF-KB, and NKILA (Table 4).

long non-coding RNA (NKILA, LINC00993) and cytokines (NF-KP, CXCL-1) as a Potential Biomarkers in breast cancer

The sensitivity and specificity of studied parameters expression levels as biomarkers in breast cancer, were assessed in the breast cancer tissues using ROC curve analysis. ROC curve analysis indicated that long non-coding RNA (NKILA, LINC00993) expression levels could be considered a diagnostic parameter for breast cancer with a sensitivity (90.6%, 92.2% respectively) and specificity (85.9%, 84.4% respectively). Cytokines (NF-KP, CXCL-1) expression levels could be considered a diagnostic parameter for breast cancer with a sensitivity (87.5%, 89.1% respectively) and specificity (89.1%, 87.5% respectively) (Table 5).

Breast cancer is the most common cancer in women and represents the leading cause of cancer mortality among this gender worldwide. It stands as the most frequent malignancy in females, thus signifying a principal focus of biomedical research [11].

The prevalence and incidence rates of breast cancer are progressively escalating across all global regions. The National Cancer Registry Program's 2013 report in Egypt reveals that breast cancer is the most pervasive form of cancer among females, accounting for 32% of all female cancer cases. [12, 13].

Innovative biomarkers are required for early detection, treatment, and prognosis. Non-coding RNAs (ncRNAs) have emerged as crucial players in various stages of breast cancer tumorigenesis, influencing cell death, metabolism, epithelial-mesenchymal transition (EMT), metastasis, and drug resistance [14].

The current study showed a significant decrease in expression levels of long non-coding RNA (NKILA) in tumour tissue compared to normal tissue (p < 0.001). NKILA expression levels in tissues showed high sensitivity and specificity, so had a significant diagnostic value for breast cancer patients.

In consistent with our results, Studies by Di Huang and colleagues, Li-Hua Luo and colleagues also reported a decrease in NKILA expression in breast cancer tissues and its involvement in inhibiting tumor progression, including cell proliferation, migration, and angiogenesis, indicating its potential as a therapeutic target [15, 16]. Our finding aligns with several other studies in various cancer types, such as non-small cell lung cancer, melanoma, hepatocellular carcinoma (HCC), and rectal cancer, where NKILA expression was also found to be downregulated in tumor tissues [17–20].

The current study observed that altered NKILA expression was associated with specific tumor characteristics in breast cancer, including positive family history, invasive lobular carcinoma, high-grade tumors, negative estrogen and progesterone receptors, and advanced lymph node involvement. These findings suggest that NKILA could serve as an important biomarker in breast cancer diagnosis and prognosis.

Consistent with our results Huang and colleagues found that NKILA levels were decreased in breast cancerous tissue compared to non-cancerous tissues and were correlated with lymph node involvement and higher TNM stage [15]. Moreover, Studies by Luo and Wu reported correlations between NKILA expression and clinical stage, TNM classification, and epithelial-mesenchymal transition (EMT) features [21, 16]. Liu and colleagues found that NKILA expression was independent prognostic factor. Furthermore, low NKILA expression is associated with breast cancer metastasis and poor patient prognosis which confirm our results [22].

NF-KP was significantly increased in in tumor tissue compared to normal tissue (p < 0.001) and a significant negative correlation between NKILA and NF-KB in breast cancer was found. This suggests a regulatory interplay between these molecules, where higher NKILA expression is associated with lower NF-KB expression and vice versa. This inverse correlation may indicate that NKILA has a potential inhibitory role in suppressing NF-KB activity, which plays a critical role in cancer-related processes, thereby affecting breast cancer pathogenesis. In accordance with our findings, Huang et al., have demonstrated that NKILA interacts with the NF-κB–IκBα complex by binding to p65 and modulates T cell activation-induced cell death by inhibiting NF-κB activity [15].

The current study has demonstrated an increase in CXCL-1 expression in breast cancer tissue as compared to normal tissue (p < 0.001). This elevation was particularly prominent in cases characterized by tumour sizes exceeding 5, invasive lobular carcinoma (ILC) type, cases graded as 3, and those with tumour stages classified as T3 or T4. These findings underscore the upregulation of CXCL-1 in breast cancer, specifically in aggressive subtypes.

These findings were in line with Wang et al., who found a correlation between elevated CXCL1 expression and advanced cancer stage, lymph node metastasis, and poor survival. The study's findings brought attention to the value of the CXCL1-NF-κB axis in propelling breast cancer growth and metastasis [23].

This prove that CXCL1 and NF-κB may serve as a potential therapeutic target for the prevention of cancer growth metastasis.

The current study found a highly significant decrease in LINC00993 expression in breast cancer tumour tissues compared to normal tissues (p < 0.001). LINC00993 expression levels in tissues showed high sensitivity and specificity, so had a significant diagnostic value for breast cancer patients.

In accordance with our results [24, 8, 25] reported significant downregulation of LINC00993 in triple-negative breast cancer (TNBC) and its association with luminal breast cancer.

The study by Guo et al. found that higher expression of LINC00993 was associated with a better outcome in TNBC patients, indicating its prognostic value [8].

Our study found that expression of LINC00993 was associated with invasive lobular carcinoma (ILC) type, high-grade tumours (Grade 3), and advanced lymph node involvement (N3). These findings suggest LINC00993 may have a significant role in breast cancer pathogenesis as their expression levels are associated with specific tumour characteristics. Chen et al., has demonstrated discernible patterns of LINC00993 expression across various subtypes of breast cancer, thereby underscoring its potential significance in distinguishing between different types of breast cancer. These findings are consistent with the results of our own study [25].

The current investigation has a positive correlation between the expression levels of NKILA and LINC00993 in cases of breast cancer. This finding suggests a potential for these lncRNAs to regulate the pathogenesis of breast cancer. The observed positive correlation supports the notion that NKILA and LINC00993 may function in concert to influence cancer-related pathways or mechanisms in breast cancer. These lncRNAs hold promise as tumour biomarkers of value and therapeutic targets for personalized breast cancer treatment strategies.

These findings suggest that LncRNAs (NKILA, LINC00993) and cytokines (NF-KB and CXCL-1) can be used as novel biomarkers for breast cancer.

Our study is a preliminary study in the Egyptian population; we concluded that LncRNAs (NKILA, LINC00993) and cytokines (NF-KB and CXCL-1) have potential diagnostic value with adequate sensitivity and specificity for breast cancer and could be considered as a valuable marker for breast cancer diagnosis. Also, they may be a promising prognostic tumour marker, and its determination could select candidate patients to a more aggressive adjuvant treatment or use the novel therapeutics options for the correction of the abnormal expressions.

Recommendation

Future larger studies are needed to confirm our findings and to further explore the existing potential of studied parameters as novel biomarkers for breast cancer in order to be utilized in the clinical field.

Author Contribution

R M provided the conception and design of this study and drafted the manuscript. A A worked on the investigation, and data collection and drafted the manuscript. M A worked on data collection and investigation. H E worked on the investigation and performed data analysis. All authors read and approved the final manuscript.

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Table (1): The primer sequences used for qRT-PCR

Name	Forward Primer	Reverse Primer
NKILA	CTTTGGAGGAGTCCAAGCGT	GTGGCTCCAAGAGTGAGCTT
LINC00993	GGCCAAGCACATCTGCAAAA	CCACTGCTTTTCCCAGGACT
NFκB	GGGGATGGTGAGAAGGTTGG	GCAGTGCCATCTGTGGTTGA
CXCL1	TGGCTTAGAACAAAGGGGCT	AAGGTAGCCCTTGTTTCCCC
Gapdh	CCATGGGGAAGGTGAAGGTC	CTTCCCGTTCTCAGCCATGT

Table (2): Expression levels of Long non-coding RNA (NKILA- LINC00993) NF-KP and CXCL-1 among the studied cases:

Variable	Tumor tissue (n=64)	Normal tissue (n=64)	P
NKILA	0.32±0.22	0.97±0.22	<0.001
LINC00993	0.51±0.19	0.97±0.14	<0.001
NFKP	5.47±2.38	1.22±0.66	<0.001
CXCL-1	5.43±2.61	1.25±0.69	<0.001

Table (3): Relation between family history, clinicopathological parameters, and studied parameters

NKILA

LINC00993

NF-KB

CXCL-1

Family history

-ve

+ve

0.42

0.22**

0.52

0.47

5.6

5.43

5.82

4.86

Tumor size

< 5

≥ 5

0.28

0.22

0.49

0.47

5.54

5.60

4.17

6.59*

Tumor type

IDC

ILC

0.28

0.12*

0.50

0.34*

5.60

4.69

4.86

7.42*

Tumor grade

1 or 2

0.30

0.12**

0.51

0.34**

5.78

4.69

4.86

6.73*

T3 or 4

0.28

0.22

0.49

0.47

5.54

5.60

4.57

6.59*

ER, PR

-ve

+ve

0.23

0.75**

0.49

0.41

5.82

5.43*

5.03

5.82

0.79

0.28

0.12**

0.52

0.36

0.34

4.2

5.54

6.54*

5.82

4.57

6.73

*: P<0.05 **: p<0.001

NKILA, NF-kB interacting long noncoding RNA; LINC00993, Long intergenic non-protein coding RNA 00993; NFκB, Nuclear Factor kappa –light- chain- enhancer of activated B cells; CXCL1, C-X-C motif chemokine ligand 1. Tumors we regraded according to the modiﬁed Bloom–Richardson system; T size of the tumor, T2 (2–5 cm), T3 (>5 cm), T4 (inﬁltration of the chest wall/skin), N regional lymph node involvement, N1 cancer has spread to one to three axillary lymph node(s), and/or tiny amounts of cancer are found in internal mammary lymph nodes on lymph node biopsy, N2 cancer has spread to four to nine axillary lymph nodes, or cancer has enlarged the internal mammary lymph nodes, N3 cancer has spread to axillary lymph nodes, the internal mammary lymph nodes and/or infraclavicular and supraclavicular lymph nodes; ER and PR, estrogen receptor and progesterone receptor.

Table (4): Correlation between Long non-coding RNA, NF-KP, and CXCL-1 among the studied cases:

	NKILA	LINC00993	NF-KP
LINC00993	0.63**
NFKP	-0.29*	0.04
CXCL-1	-0.10	-0.23	0.10

*: P<0.05 **: p<0.001

Table (5): Validity of studied parameter in the diagnosis of tumor among the studied cases:

	Cut off	AUC (CI 95%)	Sensitivity	Specificity	PPV	NPV	Accuracy	p
NKILA	<0.75	0.97 (0.94-1)	90.6%	85.9%	86.6%	90.1%	87.5%	<0.001
LINC00993	<0.88	0.97 (0.95-0.99)	92.2%	84.4%	85.5%	91.5%	88.3%	<0.001
NF-KB	>2.05	0.95 (0.91-0.99)	87.5%	89.1%	88.9%	87.7%	85.9%	<0.001
CXCL-1	>1.16	0.96 (0.93-0.99)	89.1%	87.5%	87.7%	88.9%	85.9%	<0.001

AUC: Area under curve, CI: Confidence interval, PPV:+ve predicted value, NPV:-ve predicted value, NKILA, NF-kB interacting long noncoding RNA; LINC00993, Long intergenic non-protein coding RNA 00993; NFκB, Nuclear Factor kappa –light- chain- enhancer of activated B cells; CXCL1, C-X-C motif chemokine ligand 1.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

The Role of Long Non-coding RNA (NKILA and LINC00993) as Tumour Biomarkers in Breast Cancer

Status:

Version 1

Abstract

Background

Aim of the work:

Subjects and methods:

Results

Conclusion

Introduction

Subjects and methods

Sample collection and RNA Isolation

Conversion of RNA into cDNA (complementary DNA)

Real-Time RT-PCR

Statistical Analysis

Results

Discussion

Conclusion

Declarations

Author Contribution

References

Tables

Additional Declarations

Status:

Version 1