Background: HIFA-AS1, an antisense transcript of HIF1α gene, is a 652 bp long noncoding RNA (lncRNA) which globally expressed in multiple tissues of animals. Recent evidence indicate d that the HIFA-AS1 was involved in tumorigenesis of several types of cancer, but there were no report s on pancreatic cancer (PC).
Results: In order to investigate whether the HIFA-AS1 could mediate the PC or not, it was overexpressed in a PC cell line (PANC-1), and a series of experiments including cell viability detection, flow cytometry transwell migration, clone formation and wound healing were performed. Functionally, the results indicated that overexpression (OE) of HIFA-AS1 could inhibit proliferation and shift, and promote apoptosis of PC cells. Moreover, to explore underlying molecular mechanism of anti tumorigenic actions of HIFA-AS1 in PC cells, the iTRAQ (isobaric tags for relative and absolute quantification) quantitative proteomics analysis was implemented and the results indicated that OE of HIFA-AS1 globally affected the expression levels of multiple protein associated with metabolism of cancer. Moreover, the network analysis revealed that the most of these differentially expressed proteins (DEPs) were integrated, and severed essential roles in regulatory function.
Conclusions: In summary, HIFA-AS1 may exhibit a potential therapeutic effect on PC, and our study provided useful information in this filed.

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The full text of this article is available to read as a PDF.
No competing interests reported.
This is a list of supplementary files associated with this preprint. Click to download.
Table 2 The all original data from the iTRAQ was analyzed using parameters
Table 3 The 183 up regulated DEPs were analyzed in OE VS NC
Table 4 The 155 down regulated DEPs were analyzed in OE VS NC
Supplementary . The all original data include d Table 2 Table 3 and Table 4
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Posted 10 Jun, 2021
On 11 Jul, 2021
Received 18 Jun, 2021
On 11 Jun, 2021
Invitations sent on 09 Jun, 2021
On 09 Jun, 2021
On 09 Jun, 2021
On 09 Jun, 2021
On 17 May, 2021
Posted 10 Jun, 2021
On 11 Jul, 2021
Received 18 Jun, 2021
On 11 Jun, 2021
Invitations sent on 09 Jun, 2021
On 09 Jun, 2021
On 09 Jun, 2021
On 09 Jun, 2021
On 17 May, 2021
Background: HIFA-AS1, an antisense transcript of HIF1α gene, is a 652 bp long noncoding RNA (lncRNA) which globally expressed in multiple tissues of animals. Recent evidence indicate d that the HIFA-AS1 was involved in tumorigenesis of several types of cancer, but there were no report s on pancreatic cancer (PC).
Results: In order to investigate whether the HIFA-AS1 could mediate the PC or not, it was overexpressed in a PC cell line (PANC-1), and a series of experiments including cell viability detection, flow cytometry transwell migration, clone formation and wound healing were performed. Functionally, the results indicated that overexpression (OE) of HIFA-AS1 could inhibit proliferation and shift, and promote apoptosis of PC cells. Moreover, to explore underlying molecular mechanism of anti tumorigenic actions of HIFA-AS1 in PC cells, the iTRAQ (isobaric tags for relative and absolute quantification) quantitative proteomics analysis was implemented and the results indicated that OE of HIFA-AS1 globally affected the expression levels of multiple protein associated with metabolism of cancer. Moreover, the network analysis revealed that the most of these differentially expressed proteins (DEPs) were integrated, and severed essential roles in regulatory function.
Conclusions: In summary, HIFA-AS1 may exhibit a potential therapeutic effect on PC, and our study provided useful information in this filed.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6
The full text of this article is available to read as a PDF.
No competing interests reported.
This is a list of supplementary files associated with this preprint. Click to download.
Table 2 The all original data from the iTRAQ was analyzed using parameters
Table 3 The 183 up regulated DEPs were analyzed in OE VS NC
Table 4 The 155 down regulated DEPs were analyzed in OE VS NC
Supplementary . The all original data include d Table 2 Table 3 and Table 4
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